bitnet

bitnet is based on Microsoft's BitNet b1.58 2B4T, a binarized LLaMa3-style LLM (ternary‐weight STE, per‐token 8-bit abs-max activation, SubLN, ReLU² FFN, RoPE / GQA attention, no biases) with 2.4B parameters trained on four trillion tokens.

tldr; No more floats. Just weights in [1, 0, -1].

Setup

chmod +x setup.sh
./setup.sh
source venv/bin/activate

Papers

04/14/2025 BitNet Official 2B Parameter Model on Hugging Face
02/18/2025 Bitnet.cpp: Efficient Edge Inference for Ternary LLMs
11/08/2024 BitNet a4.8: 4-bit Activations for 1-bit LLMs
10/21/2024 1-bit AI Infra: Part 1.1, Fast and Lossless BitNet b1.58 Inference on CPUs
03/21/2024 The-Era-of-1-bit-LLMs__Training_Tips_Code_FAQ
02/27/2024 The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
10/17/2023 BitNet: Scaling 1-bit Transformers for Large Language Models

Notes

Notes from HF model card

Parameters: 2,412,820,480 (2.4B)
Context Length: 4096 tokens
Weights: 1.58-bit with 8-bit activations (W1.58A8)
Model: Based off of LLaMa
- Modified with BitLinear layers
- Uses Rotary Position Embeddings (RoPE).
- Uses squared ReLU (ReLU²) activation in FFN layers
- Employs Sub-LayerNorm normalization
- No bias terms in linear or normalization layers
  - Binarization is a form of regularization. By reducing precision, the model generalizes better
Tokenizer: LLaMA 3 Tokenizer (vocab size: 128,256)
STE: Straight-through-Estimator to approximate gradients for non-differentiable functions like clip()
Quantization Function: It first scales the weight matrix by its average absolute value, and then rounds each value to the nearest integer among {-1, 0, +1}
Binarized LLMs training loss curve follow an S shape

Model Architecture

config.json:

{
  "architectures": [
    "BitNetForCausalLM"
  ],
  "auto_map": {
    "AutoConfig": "configuration_bitnet.BitNetConfig",
    "AutoModelForCausalLM": "modeling_bitnet.BitNetForCausalLM"
  },
  "bos_token_id": 128000,
  "eos_token_id": 128001,
  "hidden_act": "relu2",
  "hidden_size": 2560,
  "initializer_range": 0.02,
  "intermediate_size": 6912,
  "max_position_embeddings": 4096,
  "model_type": "bitnet",
  "rms_norm_eps": 1e-05,
  "num_attention_heads": 20,
  "num_hidden_layers": 30,
  "num_key_value_heads": 5,
  "rope_theta": 500000.0,
  "tie_word_embeddings": true,
  "torch_dtype": "bfloat16",
  "use_cache": true,
  "vocab_size": 128256,
  "quantization_config": {
    "quant_method": "bitnet",
    "linear_class": "autobitlinear",
    "quantization_mode": "online"
  }
}

Layer Info (2,412,820,480 parameters)

[Layer name]                                    [Weight shape]             [#Params] [Sample weights]
model.embed_tokens.weight                       torch.Size([128256, 2560]) 328335360 [-0.45703125, 0.90625, 0.69140625, 0.73046875, -0.171875]
model.layers.0.input_layernorm.weight           torch.Size([2560])         2560      [0.0174560546875, 0.0179443359375, 0.019287109375, 0.0274658203125, 0.01300048828125]
model.layers.0.mlp.down_proj.weight             torch.Size([2560, 6912])   17694720  [-1.1328125, -0.46484375, 6.40625, -1.5703125, 0.77734375]
model.layers.0.mlp.ffn_sub_norm.weight          torch.Size([6912])         6912      [1.1875, 1.1953125, 1.3046875, 0.69140625, 3.234375]
model.layers.0.mlp.gate_proj.weight             torch.Size([6912, 2560])   17694720  [0.7734375, 1.84375, 1.15625, -0.6640625, 0.77734375]
model.layers.0.mlp.up_proj.weight               torch.Size([6912, 2560])   17694720  [0.58984375, 2.546875, -1.625, -0.8984375, -5.1875]
model.layers.0.post_attention_layernorm.weight  torch.Size([2560])         2560      [1.34375, 1.3359375, 1.3203125, 1.5703125, 1.2265625]
model.layers.0.self_attn.attn_sub_norm.weight   torch.Size([2560])         2560      [0.0128173828125, 0.0166015625, 0.0152587890625, 0.01513671875, 0.01495361328125]
model.layers.0.self_attn.k_proj.weight          torch.Size([640, 2560])    1638400   [-0.90625, -0.890625, 2.953125, -4.8125, 0.89453125]
model.layers.0.self_attn.o_proj.weight          torch.Size([2560, 2560])   6553600   [-0.458984375, 0.482421875, -4.25, -3.015625, -2.671875]
model.layers.0.self_attn.q_proj.weight          torch.Size([2560, 2560])   6553600   [0.59765625, -0.1904296875, 0.45703125, -2.6875, -0.60546875]
model.layers.0.self_attn.v_proj.weight          torch.Size([640, 2560])    1638400   [7.15625, 1.171875, -0.54296875, 1.1640625, 0.95703125]
model.layers.1.input_layernorm.weight           torch.Size([2560])         2560      [0.016845703125, 0.01531982421875, 0.0172119140625, 0.01409912109375, 0.01611328125]
model.layers.1.mlp.down_proj.weight             torch.Size([2560, 6912])   17694720  [-1.1886598875514971e-34, -2.3773197751029943e-34, 0.63671875, 0.57421875, -4.152786442584977e-34]
model.layers.1.mlp.ffn_sub_norm.weight          torch.Size([6912])         6912      [1.0159280456642669e-32, 1.0785207688568521e-32, 2.28125, 0.4453125, 1.0592614694129797e-32]
model.layers.1.mlp.gate_proj.weight             torch.Size([6912, 2560])   17694720  [-6.229179663877466e-34, -3.2048677980818847e-34, -3.445609041130289e-34, -5.657419211637505e-34, 7.342607912976337e-34]
model.layers.1.mlp.up_proj.weight               torch.Size([6912, 2560])   17694720  [2.3321807920314184e-34, 7.748858760620519e-35, -9.930576275746685e-35, -4.739593222515463e-35, -3.385423730368188e-34]
model.layers.1.post_attention_layernorm.weight  torch.Size([2560])         2560      [1.3203125, 1.328125, 1.203125, 1.234375, 1.1875]
model.layers.1.self_attn.attn_sub_norm.weight   torch.Size([2560])         2560      [0.2060546875, 0.330078125, 0.318359375, 0.2890625, 0.291015625]
model.layers.1.self_attn.k_proj.weight          torch.Size([640, 2560])    1638400   [0.66796875, -4.90625, -0.67578125, -0.0157470703125, 0.6875]
model.layers.1.self_attn.o_proj.weight          torch.Size([2560, 2560])   6553600   [-0.796875, -0.328125, -4.0625, 0.5078125, 3.734375]
model.layers.1.self_attn.q_proj.weight          torch.Size([2560, 2560])   6553600   [-0.1669921875, -0.416015625, -0.1689453125, 0.4140625, 0.40625]
model.layers.1.self_attn.v_proj.weight          torch.Size([640, 2560])    1638400   [1.3046875, -0.006378173828125, 0.076171875, 1.125, 1.125]
model.layers.2.input_layernorm.weight           torch.Size([2560])         2560      [0.0205078125, 0.0184326171875, 0.0166015625, 0.01904296875, 0.0185546875]
model.layers.2.mlp.down_proj.weight             torch.Size([2560, 6912])   17694720  [2.421875, 9.103028252767794e-35, 0.2392578125, -3.325238419606087e-34, 4.78125]
model.layers.2.mlp.ffn_sub_norm.weight          torch.Size([6912])         6912      [0.75390625, 1.1651876163542777e-32, 0.3828125, 1.1700024412152458e-32, 0.8828125]
model.layers.2.mlp.gate_proj.weight             torch.Size([6912, 2560])   17694720  [2.421875, 0.56640625, -0.640625, 0.5546875, -0.255859375]
model.layers.2.mlp.up_proj.weight               torch.Size([6912, 2560])   17694720  [2.1875, 0.51171875, -0.82421875, -0.470703125, 0.50390625]
model.layers.2.post_attention_layernorm.weight  torch.Size([2560])         2560      [1.2890625, 1.296875, 1.140625, 1.2734375, 1.1796875]
model.layers.2.self_attn.attn_sub_norm.weight   torch.Size([2560])         2560      [0.45703125, 0.4921875, 0.45703125, 0.419921875, 0.5]
model.layers.2.self_attn.k_proj.weight          torch.Size([640, 2560])    1638400   [-0.625, -0.189453125, -0.75390625, 2.78125, -2.234375]
model.layers.2.self_attn.o_proj.weight          torch.Size([2560, 2560])   6553600   [2.609375, -4.0, -0.7734375, -0.96484375, 2.25]
model.layers.2.self_attn.q_proj.weight          torch.Size([2560, 2560])   6553600   [0.5, 0.50390625, 0.63671875, 0.423828125, -0.578125]
model.layers.2.self_attn.v_proj.weight          torch.Size([640, 2560])    1638400   [1.0234375, 1.6875, -0.94921875, -0.76953125, -6.5]
model.layers.3.input_layernorm.weight           torch.Size([2560])         2560      [0.021484375, 0.0194091796875, 0.0205078125, 0.0181884765625, 0.018798828125]
model.layers.3.mlp.down_proj.weight             torch.Size([2560, 6912])   17694720  [1.0078125, -3.46875, -0.77734375, 5.34375, 5.4072740137825225e-37]
model.layers.3.mlp.ffn_sub_norm.weight          torch.Size([6912])         6912      [0.65625, 0.890625, 0.921875, 0.921875, 1.1459283169104053e-32]
model.layers.3.mlp.gate_proj.weight             torch.Size([6912, 2560])   17694720  [4.5, -7.9375, 0.875, 4.46875, 0.921875]
model.layers.3.mlp.up_proj.weight               torch.Size([6912, 2560])   17694720  [1.8671875, -0.98046875, -1.6953125, 2.328125, 1.296875]
model.layers.3.post_attention_layernorm.weight  torch.Size([2560])         2560      [1.3046875, 1.359375, 1.1796875, 1.3125, 1.21875]
model.layers.3.self_attn.attn_sub_norm.weight   torch.Size([2560])         2560      [0.4140625, 0.31640625, 0.39453125, 0.38671875, 0.419921875]
model.layers.3.self_attn.k_proj.weight          torch.Size([640, 2560])    1638400   [0.59765625, 0.002410888671875, 0.1875, 0.765625, 0.546875]
model.layers.3.self_attn.o_proj.weight          torch.Size([2560, 2560])   6553600   [-1.265625, 0.765625, -0.9765625, 3.34375, -5.5]
model.layers.3.self_attn.q_proj.weight          torch.Size([2560, 2560])   6553600   [0.7265625, 0.515625, -5.5, -0.4765625, 0.486328125]
model.layers.3.self_attn.v_proj.weight          torch.Size([640, 2560])    1638400   [1.390625, 4.8125, -1.25, 1.3515625, -5.34375]
model.layers.4.input_layernorm.weight           torch.Size([2560])         2560      [0.0186767578125, 0.0185546875, 0.0177001953125, 0.019775390625, 0.0162353515625]
model.layers.4.mlp.down_proj.weight             torch.Size([2560, 6912])   17694720  [1.0703125, -1.078125, 2.90625, -0.84765625, -0.9453125]
model.layers.4.mlp.ffn_sub_norm.weight          torch.Size([6912])         6912      [0.7421875, 0.2314453125, 0.5390625, 0.8984375, 1.0390625]
model.layers.4.mlp.gate_proj.weight             torch.Size([6912, 2560])   17694720  [-0.1650390625, 1.046875, -2.90625, -1.0546875, -0.353515625]
model.layers.4.mlp.up_proj.weight               torch.Size([6912, 2560])   17694720  [2.484375, 0.75, -0.9765625, -0.294921875, -4.25]
model.layers.4.post_attention_layernorm.weight  torch.Size([2560])         2560      [1.3125, 1.3671875, 1.2109375, 1.3046875, 1.2109375]
model.layers.4.self_attn.attn_sub_norm.weight   torch.Size([2560])         2560      [0.322265625, 0.302734375, 0.357421875, 0.3984375, 0.26953125]
model.layers.4.self_attn.k_proj.weight          torch.Size([640, 2560])    1638400   [0.90625, 1.0390625, 0.7421875, 0.5703125, -1.6953125]
model.layers.4.self_attn.o_proj.weight          torch.Size([2560, 2560])   6553600   [-2.5625, 1.4140625, 1.0625, -1.0703125, -1.265625]
model.layers.4.self_attn.q_proj.weight          torch.Size([2560, 2560])   6553600   [-0.5, -0.1416015625, -0.01458740234375, 0.46484375, 0.47265625]
model.layers.4.self_attn.v_proj.weight          torch.Size([640, 2560])    1638400   [1.515625, -1.53125, -2.0, 1.6171875, -1.8046875]
model.layers.5.input_layernorm.weight           torch.Size([2560])         2560      [0.0155029296875, 0.015869140625, 0.01611328125, 0.0145263671875, 0.01507568359375]
model.layers.5.mlp.down_proj.weight             torch.Size([2560, 6912])   17694720  [0.057373046875, -7.28125, 1.921875, 3.765625, -0.8125]
model.layers.5.mlp.ffn_sub_norm.weight          torch.Size([6912])         6912      [1.84375, 0.94921875, 0.70703125, 1.046875, 1.078125]
model.layers.5.mlp.gate_proj.weight             torch.Size([6912, 2560])   17694720  [0.90625, 1.6171875, 3.546875, -3.640625, 1.140625]
model.layers.5.mlp.up_proj.weight               torch.Size([6912, 2560])   17694720  [2.96875, 1.0078125, -0.11767578125, -0.67578125, 3.875]
model.layers.5.post_attention_layernorm.weight  torch.Size([2560])         2560      [1.34375, 1.3984375, 1.2265625, 1.34375, 1.2421875]
model.layers.5.self_attn.attn_sub_norm.weight   torch.Size([2560])         2560      [0.625, 0.5546875, 0.546875, 0.64453125, 0.5546875]
model.layers.5.self_attn.k_proj.weight          torch.Size([640, 2560])    1638400   [-0.97265625, -6.75, -0.80859375, -0.88671875, 0.97265625]
model.layers.5.self_attn.o_proj.weight          torch.Size([2560, 2560])   6553600   [-2.515625, -1.046875, -4.34375, -1.0859375, 1.0625]
model.layers.5.self_attn.q_proj.weight          torch.Size([2560, 2560])   6553600   [0.72265625, 0.6328125, -0.4609375, -0.54296875, -0.6484375]
model.layers.5.self_attn.v_proj.weight          torch.Size([640, 2560])    1638400   [0.1767578125, 1.3046875, -7.375, 4.46875, -4.28125]
model.layers.6.input_layernorm.weight           torch.Size([2560])         2560      [0.017822265625, 0.0159912109375, 0.0184326171875, 0.0179443359375, 0.016357421875]
model.layers.6.mlp.down_proj.weight             torch.Size([2560, 6912])   17694720  [-1.1640625, 0.025634765625, 1.140625, -3.015625, 0.8359375]
model.layers.6.mlp.ffn_sub_norm.weight          torch.Size([6912])         6912      [0.5625, 0.271484375, 1.640625, 0.1826171875, 0.53125]
model.layers.6.mlp.gate_proj.weight             torch.Size([6912, 2560])   17694720  [-4.28125, 1.0390625, -0.765625, 1.3984375, -6.78125]
model.layers.6.mlp.up_proj.weight               torch.Size([6912, 2560])   17694720  [-0.4296875, -0.91015625, -0.3046875, 0.5859375, 0.267578125]
model.layers.6.post_attention_layernorm.weight  torch.Size([2560])         2560      [1.3515625, 1.421875, 1.296875, 1.359375, 1.2421875]
model.layers.6.self_attn.attn_sub_norm.weight   torch.Size([2560])         2560      [0.64453125, 0.6484375, 0.58203125, 0.64453125, 0.60546875]
model.layers.6.self_attn.k_proj.weight          torch.Size([640, 2560])    1638400   [-1.09375, 0.478515625, -1.0625, 0.283203125, -1.078125]
model.layers.6.self_attn.o_proj.weight          torch.Size([2560, 2560])   6553600   [-1.3515625, 0.51171875, 1.171875, 0.65625, 1.1796875]
model.layers.6.self_attn.q_proj.weight          torch.Size([2560, 2560])   6553600   [0.5546875, 2.0625, 0.67578125, 0.80859375, 0.671875]
model.layers.6.self_attn.v_proj.weight          torch.Size([640, 2560])    1638400   [1.734375, 1.234375, -1.71875, -0.470703125, -1.7421875]
model.layers.7.input_layernorm.weight           torch.Size([2560])         2560      [0.0166015625, 0.0157470703125, 0.0150146484375, 0.015869140625, 0.01495361328125]
model.layers.7.mlp.down_proj.weight             torch.Size([2560, 6912])   17694720  [1.1953125, 1.1875, -3.109375, 0.2421875, -0.138671875]
model.layers.7.mlp.ffn_sub_norm.weight          torch.Size([6912])         6912      [0.734375, 1.6015625, 1.4609375, 0.98046875, 1.0390625]
model.layers.7.mlp.gate_proj.weight             torch.Size([6912, 2560])   17694720  [-2.046875, 0.98046875, 1.015625, 0.9609375, 0.11669921875]
model.layers.7.mlp.up_proj.weight               torch.Size([6912, 2560])   17694720  [0.765625, 0.875, 1.0703125, -1.296875, -2.5]
model.layers.7.post_attention_layernorm.weight  torch.Size([2560])         2560      [1.359375, 1.3984375, 1.3203125, 1.359375, 1.25]
model.layers.7.self_attn.attn_sub_norm.weight   torch.Size([2560])         2560      [0.7109375, 0.77734375, 0.8359375, 0.80078125, 0.828125]
model.layers.7.self_attn.k_proj.weight          torch.Size([640, 2560])    1638400   [-0.412109375, -1.125, -1.140625, -0.86328125, 0.5546875]
model.layers.7.self_attn.o_proj.weight          torch.Size([2560, 2560])   6553600   [-3.796875, -0.85546875, -12.4375, -1.125, 2.953125]
model.layers.7.self_attn.q_proj.weight          torch.Size([2560, 2560])   6553600   [-0.80859375, 0.396484375, -0.703125, -0.671875, -0.265625]
model.layers.7.self_attn.v_proj.weight          torch.Size([640, 2560])    1638400   [-2.921875, -0.9609375, 1.6171875, 0.59375, -1.6015625]
model.layers.8.input_layernorm.weight           torch.Size([2560])         2560      [0.0169677734375, 0.01708984375, 0.0166015625, 0.0167236328125, 0.01513671875]
model.layers.8.mlp.down_proj.weight             torch.Size([2560, 6912])   17694720  [6.8125, 1.2734375, -1.171875, 5.0, -1.3125]
model.layers.8.mlp.ffn_sub_norm.weight          torch.Size([6912])         6912      [1.0859375, 0.51171875, <
F41A
span class="pl-c1">0.90234375, 0.5078125, 0.95703125]
model.layers.8.mlp.gate_proj.weight             torch.Size([6912, 2560])   17694720  [-2.140625, 1.1328125, -0.65625, -0.1025390625, 0.6875]
model.layers.8.mlp.up_proj.weight               torch.Size([6912, 2560])   17694720  [0.9453125, -3.890625, 0.84765625, -0.94921875, -3.1875]
model.layers.8.post_attention_layernorm.weight  torch.Size([2560])         2560      [1.359375, 1.375, 1.3046875, 1.359375, 1.234375]
model.layers.8.self_attn.attn_sub_norm.weight   torch.Size([2560])         2560      [0.90625, 0.84375, 0.9296875, 0.87890625, 0.89453125]
model.layers.8.self_attn.k_proj.weight          torch.Size([640, 2560])    1638400   [-1.140625, 1.0703125, -0.11865234375, 1.7265625, 1.140625]
model.layers.8.self_attn.o_proj.weight          torch.Size([2560, 2560])   6553600   [-1.09375, -1.3203125, 0.439453125, -1.3125, -3.703125]
model.layers.8.self_attn.q_proj.weight          torch.Size([2560, 2560])   6553600   [0.50390625, 0.78515625, 0.671875, 0.57421875, 0.7265625]
model.layers.8.self_attn.v_proj.weight          torch.Size([640, 2560])    1638400   [2.5, 7.75, 13.125, 7.3125, -8.375]
model.layers.9.input_layernorm.weight           torch.Size([2560])         2560      [0.01300048828125, 0.01470947265625, 0.01263427734375, 0.0152587890625, 0.0123291015625]
model.layers.9.mlp.down_proj.weight             torch.Size([2560, 6912])   17694720  [1.203125, -3.46875, -1.3125, -1.6796875, -1.3125]
model.layers.9.mlp.ffn_sub_norm.weight          torch.Size([6912])         6912      [1.046875, 3.8125, 2.546875, 0.83984375, 1.9609375]
model.layers.9.mlp.gate_proj.weight             torch.Size([6912, 2560])   17694720  [-0.69921875, 1.09375, 8.0, 0.92578125, -2.0]
model.layers.9.mlp.up_proj.weight               torch.Size([6912, 2560])   17694720  [6.8125, 0.95703125, -1.6328125, 2.25, 1.078125]
model.layers.9.post_attention_layernorm.weight  torch.Size([2560])         2560      [1.296875, 1.2578125, 1.28125, 1.3203125, 1.1875]
model.layers.9.self_attn.attn_sub_norm.weight   torch.Size([2560])         2560      [0.8125, 0.83203125, 0.94140625, 0.84375, 0.8125]
model.layers.9.self_attn.k_proj.weight          torch.Size([640, 2560])    1638400   [-0.1396484375, -1.0234375, -1.1640625, -1.171875, 1.1015625]
model.layers.9.self_attn.o_proj.weight          torch.Size([2560, 2560])   6553600   [0.96484375, 2.375, -6.375, -0.93359375, 10.25]
model.layers.9.self_attn.q_proj.weight          torch.Size([2560, 2560])   6553600   [-0.7421875, 4.46875, 0.66015625, 2.53125, -0.5625]
model.layers.9.self_attn.v_proj.weight          torch.Size([640, 2560])    1638400   [10.125, 1.8125, 1.8125, 6.90625, 9.25]
model.layers.10.input_layernorm.weight          torch.Size([2560])         2560      [0.0172119140625, 0.01556396484375, 0.013916015625, 0.015869140625, 0.013427734375]
model.layers.10.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [-3.9375, 10.875, -0.31640625, -0.89453125, -1.1328125]
model.layers.10.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [3.265625, 1.3828125, 0.7578125, 1.3515625, 1.171875]
model.layers.10.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-0.73828125, -0.78515625, -0.283203125, -6.09375, 1.3125]
model.layers.10.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [-5.34375, 0.7421875, 0.91015625, -2.25, 0.98046875]
model.layers.10.post_attention_layernorm.weight torch.Size([2560])         2560      [1.296875, 1.265625, 1.28125, 1.328125, 1.21875]
model.layers.10.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [0.91015625, 0.92578125, 0.921875, 0.890625, 0.875]
model.layers.10.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [0.625, -0.609375, 1.25, 0.0791015625, 1.265625]
model.layers.10.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [-0.369140625, 1.3125, -6.78125, -1.28125, 7.8125]
model.layers.10.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [0.396484375, -0.76953125, 0.1005859375, 0.35546875, 0.78125]
model.layers.10.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [1.90625, -1.9140625, -1.9140625, 1.921875, -3.84375]
model.layers.11.input_layernorm.weight          torch.Size([2560])         2560      [0.01397705078125, 0.0157470703125, 0.0152587890625, 0.0172119140625, 0.0130615234375]
model.layers.11.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [-0.8515625, -5.875, 1.2421875, 1.234375, -1.1484375]
model.layers.11.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [1.5234375, 0.94140625, 1.71875, 0.66015625, 1.609375]
model.layers.11.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-1.03125, -3.796875, -1.0078125, -4.0, -1.3359375]
model.layers.11.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [3.421875, 6.40625, -1.015625, -1.1875, -1.0390625]
model.layers.11.post_attention_layernorm.weight torch.Size([2560])         2560      [1.3125, 1.3359375, 1.3125, 1.390625, 1.2421875]
model.layers.11.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [2.03125, 2.46875, 2.171875, 2.3125, 2.265625]
model.layers.11.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [-1.1640625, -1.265625, -1.2265625, -1.265625, 1.296875]
model.layers.11.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [6.5, 1.5625, -1.359375, -1.375, -1.5078125]
model.layers.11.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [0.5234375, 0.259765625, 0.75390625, -0.6796875, -0.61328125]
model.layers.11.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [2.53125, -0.0927734375, 0.482421875, -3.890625, -1.9921875]
model.layers.12.input_layernorm.weight          torch.Size([2560])         2560      [0.01373291015625, 0.01373291015625, 0.01422119140625, 0.0137939453125, 0.01220703125]
model.layers.12.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [0.875, -0.5, 1.296875, 9.375, -2.46875]
model.layers.12.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [2.265625, 1.6796875, 1.34375, 1.8359375, 0.74609375]
model.layers.12.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-0.94140625, -2.1875, 2.34375, -1.0390625, 3.46875]
model.layers.12.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [0.75, -0.96875, 1.28125, -0.80078125, -1.015625]
model.layers.12.post_attention_layernorm.weight torch.Size([2560])         2560      [1.3125, 1.34375, 1.28125, 1.40625, 1.203125]
model.layers.12.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [1.2734375, 1.375, 1.3984375, 1.3125, 1.3515625]
model.layers.12.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [1.0546875, -0.84765625, 0.408203125, -1.3828125, -1.1953125]
model.layers.12.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [-1.765625, 7.0, 0.87109375, 1.5703125, 8.75]
model.layers.12.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [-0.66015625, -0.828125, -0.6328125, 0.95703125, -0.91015625]
model.layers.12.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [-0.1083984375, 0.51171875, -1.9453125, -2.734375, -2.21875]
model.layers.13.input_layernorm.weight          torch.Size([2560])         2560      [0.01336669921875, 0.0133056640625, 0.01318359375, 0.0133056640625, 0.01214599609375]
model.layers.13.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [-5.9375, 0.98046875, -1.453125, 4.375, -1.21875]
model.layers.13.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [2.671875, 2.21875, 2.390625, 1.203125, 2.734375]
model.layers.13.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-1.421875, -1.046875, -1.1328125, 3.515625, -3.03125]
model.layers.13.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [0.734375, -2.921875, 0.96875, -1.3515625, 1.03125]
model.layers.13.post_attention_layernorm.weight torch.Size([2560])         2560      [1.234375, 1.2421875, 1.28125, 1.3515625, 1.171875]
model.layers.13.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [1.53125, 1.484375, 1.515625, 1.3828125, 1.5234375]
model.layers.13.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [0.059326171875, 1.265625, -1.25, 1.2421875, -0.39453125]
model.layers.13.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [0.462890625, 1.6875, 16.25, -1.75, -4.4375]
model.layers.13.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [-0.298828125, 0.8125, 0.49609375, 0.76953125, -0.8359375]
model.layers.13.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [-0.578125, 2.078125, -1.9296875, 6.09375, 2.09375]
model.layers.14.input_layernorm.weight          torch.Size([2560])         2560      [0.01336669921875, 0.0135498046875, 0.01422119140625, 0.01458740234375, 0.01324462890625]
model.layers.14.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [1.1328125, 1.25, 1.09375, 10.75, 0.32421875]
model.layers.14.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [2.890625, 2.125, 1.6015625, 2.8125, 2.390625]
model.layers.14.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-0.1875, 1.2734375, 0.71484375, 0.96875, -1.140625]
model.layers.14.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [3.625, 1.203125, 3.34375, -0.76171875, -1.515625]
model.layers.14.post_attention_layernorm.weight torch.Size([2560])         2560      [1.2578125, 1.265625, 1.2578125, 1.3828125, 1.1484375]
model.layers.14.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [2.453125, 2.21875, 2.171875, 2.25, 2.375]
model.layers.14.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [-0.1650390625, 1.5, -1.203125, 0.30078125, 1.4140625]
model.layers.14.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [1.296875, 1.25, 8.9375, -4.875, -5.25]
model.layers.14.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [0.9140625, -0.09228515625, -0.6015625, -0.42578125, 0.400390625]
model.layers.14.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [-2.09375, -3.875, -7.25, 4.28125, -18.0]
model.layers.15.input_layernorm.weight          torch.Size([2560])         2560      [0.01214599609375, 0.0157470703125, 0.01214599609375, 0.012939453125, 0.01153564453125]
model.layers.15.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [-3.28125, -1.3046875, -1.4921875, 2.15625, 4.34375]
model.layers.15.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [3.46875, 1.6015625, 1.4921875, 3.140625, 1.4609375]
model.layers.15.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-1.078125, -1.078125, -7.21875, 9.1875, -0.31640625]
model.layers.15.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [-1.046875, 1.0703125, 7.4375, 1.03125, 0.62109375]
model.layers.15.post_attention_layernorm.weight torch.Size([2560])         2560      [1.359375, 1.421875, 1.3828125, 1.484375, 1.296875]
model.layers.15.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [1.765625, 1.9375, 1.609375, 2.0625, 2.046875]
model.layers.15.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [1.2109375, -0.7578125, -1.359375, 1.3671875, -1.171875]
model.layers.15.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [1.421875, 3.640625, 3.625, -1.4140625, -1.3984375]
model.layers.15.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [-0.83203125, 0.1923828125, -0.83984375, -0.5390625, -0.84765625]
model.layers.15.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [-5.65625, -0.79296875, 8.375, -2.25, -2.25]
model.layers.16.input_layernorm.weight          torch.Size([2560])         2560      [0.0120849609375, 0.01190185546875, 0.01080322265625, 0.0128173828125, 0.010009765625]
model.layers.16.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [-1.3046875, 12.0, 1.3203125, -3.5625, 5.34375]
model.layers.16.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [2.34375, 3.109375, 1.9921875, 1.90625, 4.8125]
model.layers.16.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [5.65625, -1.109375, 0.62109375, -0.80859375, -5.3125]
model.layers.16.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [-6.90625, -1.03125, 7.1875, -0.90234375, 0.7890625]
model.layers.16.post_attention_layernorm.weight torch.Size([2560])         2560      [1.3671875, 1.4453125, 1.3671875, 1.453125, 1.296875]
model.layers.16.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [1.921875, 1.9296875, 1.9453125, 1.9453125, 2.0]
model.layers.16.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [-1.5390625, -1.2578125, 1.5625, 1.515625, -0.4765625]
model.layers.16.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [1.390625, 5.3125, -1.40625, -3.296875, -1.21875]
model.layers.16.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [-2.40625, -1.0078125, -0.921875, -0.455078125, -1.0234375]
model.layers.16.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [3.484375, -2.140625, 3.328125, 10.4375, -4.5]
model.layers.17.input_layernorm.weight          torch.Size([2560])         2560      [0.01214599609375, 0.0126953125, 0.01275634765625, 0.0125732421875, 0.01263427734375]
model.layers.17.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [-0.8359375, -12.875, -1.9296875, 6.34375, 1.34375]
model.layers.17.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [3.234375, 3.140625, 2.671875, 1.8515625, 2.171875]
model.layers.17.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-1.21875, 0.50390625, 0.8671875, -1.109375, 1.203125]
model.layers.17.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [2.484375, -1.6875, -1.0546875, -0.69140625, -3.578125]
model.layers.17.post_attention_layernorm.weight torch.Size([2560])         2560      [1.3828125, 1.4765625, 1.3984375, 1.484375, 1.3046875]
model.layers.17.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [2.625, 2.625, 2.46875, 2.59375, 2.65625]
model.layers.17.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [1.40625, -7.96875, -1.703125, -1.421875, 1.2109375]
model.layers.17.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [-2.234375, 1.609375, 4.3125, -3.484375, -1.5]
model.layers.17.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [0.6640625, -0.9765625, 0.76953125, 0.890625, 0.9765625]
model.layers.17.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [-6.375, 2.140625, 2.296875, -14.125, 3.375]
model.layers.18.input_layernorm.weight          torch.Size([2560])         2560      [0.01336669921875, 0.01531982421875, 0.01226806640625, 0.0147705078125, 0.0135498046875]
model.layers.18.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [0.4453125, -12.75, -3.640625, 1.578125, 3.640625]
model.layers.18.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [1.7578125, 4.84375, 4.40625, 3.890625, 3.71875]
model.layers.18.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-1.3515625, -2.296875, -1.296875, 1.546875, 1.1484375]
model.layers.18.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [1.375, 0.9375, 2.328125, 0.89453125, 1.09375]
model.layers.18.post_attention_layernorm.weight torch.Size([2560])         2560      [1.4140625, 1.5234375, 1.4609375, 1.546875, 1.375]
model.layers.18.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [5.03125, 4.96875, 5.15625, 5.28125, 4.0625]
model.layers.18.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [-0.031982421875, -3.390625, 1.109375, -1.2578125, -1.28125]
model.layers.18.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [1.5234375, -5.75, 1.0234375, -1.3203125, 1.3125]
model.layers.18.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [0.328125, -2.296875, -0.291015625, -0.0400390625, -0.71484375]
model.layers.18.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [-7.46875, 0.52734375, 2.140625, -3.21875, 1.484375]
model.layers.19.input_layernorm.weight          torch.Size([2560])         2560      [0.013916015625, 0.01263427734375, 0.0146484375, 0.015380859375, 0.01409912109375]
model.layers.19.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [0.21875, -1.1328125, -9.75, -8.625, 3.671875]
model.layers.19.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [2.90625, 3.109375, 4.65625, 6.25, 5.375]
model.layers.19.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-2.609375, 1.296875, 1.1875, 7.0, -10.0]
model.layers.19.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [0.98046875, -1.03125, -6.875, 1.2578125, -7.8125]
model.layers.19.post_attention_layernorm.weight torch.Size([2560])         2560      [1.421875, 1.53125, 1.4296875, 1.5390625, 1.3515625]
model.layers.19.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [3.234375, 3.296875, 3.125, 3.34375, 3.3125]
model.layers.19.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [1.1875, -2.0625, -1.265625, -1.15625, 1.1953125]
model.layers.19.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [-3.078125, 3.75, -1.375, 0.5390625, -4.84375]
model.layers.19.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [-0.8046875, -0.9609375, -0.82421875, -0.462890625, 0.8125]
model.layers.19.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [-2.21875, -0.078125, 6.53125, -9.5625, 14.5]
model.layers.20.input_layernorm.weight          torch.Size([2560])         2560      [0.01287841796875, 0.01409912109375, 0.013916015625, 0.01422119140625, 0.01226806640625]
model.layers.20.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [-1.2109375, -1.09375, -1.71875, -0.93359375, 1.25]
model.layers.20.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [3.9375, 5.4375, 6.75, 1.9375, 4.96875]
model.layers.20.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-0.94140625, 1.1640625, 1.15625, -1.15625, -1.265625]
model.layers.20.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [-1.3359375, 2.65625, -0.65625, 1.59375, -2.0625]
model.layers.20.post_attention_layernorm.weight torch.Size([2560])         2560      [1.4140625, 1.484375, 1.4609375, 1.546875, 1.3671875]
model.layers.20.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [4.84375, 4.53125, 4.625, 4.34375, 4.34375]
model.layers.20.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [-1.6640625, -1.4609375, 0.63671875, -1.4921875, 1.609375]
model.layers.20.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [-1.0078125, -4.09375, 2.734375, 6.6875, -1.234375]
model.layers.20.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [-0.9140625, -0.62890625, -0.91796875, -0.8359375, -0.97265625]
model.layers.20.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [9.6875, -4.09375, 2.109375, -3.640625, -1.9765625]
model.layers.21.input_layernorm.weight          torch.Size([2560])         2560      [0.012939453125, 0.01312255859375, 0.01312255859375, 0.0137939453125, 0.01312255859375]
model.layers.21.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [7.03125, -13.4375, -1.4140625, -2.21875, -3.234375]
model.layers.21.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [3.78125, 8.625, 3.703125, 5.21875, 6.96875]
model.layers.21.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-0.85546875, -2.375, -0.296875, 4.65625, -1.203125]
model.layers.21.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [1.7265625, -1.9140625, 7.4375, -1.46875, -0.7890625]
model.layers.21.post_attention_layernorm.weight torch.Size([2560])         2560      [1.421875, 1.484375, 1.4453125, 1.5234375, 1.359375]
model.layers.21.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [5.53125, 5.28125, 5.5, 5.65625, 5.5]
model.layers.21.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [-1.5390625, -8.4375, 0.46875, -1.390625, -1.1796875]
model.layers.21.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [1.140625, 1.4375, 1.296875, 1.234375, 1.1484375]
model.layers.21.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [0.447265625, 0.82421875, -0.42578125, 1.09375, 0.062255859375]
model.layers.21.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [5.96875, 1.9140625, -1.203125, -1.90625, -1.9140625]
model.layers.22.input_layernorm.weight          torch.Size([2560])         2560      [0.01483154296875, 0.01373291015625, 0.01513671875, 0.01458740234375, 0.01556396484375]
model.layers.22.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [2.0, 6.34375, 4.09375, -5.46875, 1.4375]
model.layers.22.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [4.59375, 4.625, 10.4375, 3.03125, 4.875]
model.layers.22.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [5.3125, 3.6875, 2.515625, -2.796875, 1.203125]
model.layers.22.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [-6.125, -4.875, -1.5859375, 1.5, 1.1328125]
model.layers.22.post_attention_layernorm.weight torch.Size([2560])         2560      [1.4296875, 1.515625, 1.4375, 1.5546875, 1.40625]
model.layers.22.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [4.65625, 4.25, 4.46875, 2.65625, 4.15625]
model.layers.22.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [1.765625, 0.9140625, -0.1728515625, 1.1875, -2.03125]
model.layers.22.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [1.2265625, -3.921875, -1.2578125, -1.8515625, -1.28125]
model.layers.22.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [-0.546875, -0.5390625, -3.375, 0.75390625, -0.03955078125]
model.layers.22.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [-0.416015625, -1.1875, 10.3125, 1.890625, -4.5625]
model.layers.23.input_layernorm.weight          torch.Size([2560])         2560      [0.01324462890625, 0.01300048828125, 0.0128173828125, 0.01416015625, 0.01470947265625]
model.layers.23.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [-1.0, 1.4609375, 0.003875732421875, -0.77734375, -13.4375]
model.layers.23.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [4.59375, 5.78125, 7.71875, 8.625, 10.5625]
model.layers.23.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [6.875, -1.1953125, -1.203125, -1.5703125, -1.4140625]
model.layers.23.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [-12.5, 2.09375, -1.125, 4.125, 0.7578125]
model.layers.23.post_attention_layernorm.weight torch.Size([2560])         2560      [1.484375, 1.5390625, 1.4609375, 1.5859375, 1.4375]
model.layers.23.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [6.5625, 6.09375, 6.3125, 6.28125, 6.65625]
model.layers.23.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [-1.3125, 1.3359375, -1.3984375, -1.3046875, 0.81640625]
model.layers.23.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [5.3125, -1.359375, 11.0625, -0.9375, 1.40625]
model.layers.23.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [0.8359375, 0.44140625, 0.48046875, -2.421875, -2.15625]
model.layers.23.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [-8.75, 1.828125, -7.15625, 1.953125, -1.8515625]
model.layers.24.input_layernorm.weight          torch.Size([2560])         2560      [0.0130615234375, 0.01190185546875, 0.01422119140625, 0.013671875, 0.01470947265625]
model.layers.24.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [1.71875, -1.453125, 5.25, -1.4609375, 10.875]
model.layers.24.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [5.0625, 5.59375, 7.3125, 8.0625, 8.3125]
model.layers.24.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [5.15625, 5.0, -3.265625, 1.1484375, 1.890625]
model.layers.24.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [1.09375, 1.109375, -1.4296875, 0.049072265625, 1.8828125]
model.layers.24.post_attention_layernorm.weight torch.Size([2560])         2560      [1.4921875, 1.5078125, 1.4921875, 1.5390625, 1.4453125]
model.layers.24.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [8.0, 8.4375, 7.8125, 7.90625, 7.34375]
model.layers.24.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [0.71875, -0.85546875, 1.6640625, -1.5625, -0.2412109375]
model.layers.24.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [-1.3984375, 1.390625, 1.3828125, -6.40625, 9.0625]
model.layers.24.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [0.023193359375, -0.80859375, -0.302734375, -0.67578125, -0.953125]
model.layers.24.self_attn.v_proj.weight         torch.Size([640, 2560<
10000
span class="pl-kos">])    1638400   [-3.90625, -7.78125, -13.125, 9.0625, 1.859375]
model.layers.25.input_layernorm.weight          torch.Size([2560])         2560      [0.0172119140625, 0.01513671875, 0.0157470703125, 0.01953125, 0.017333984375]
model.layers.25.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [1.2890625, 0.72265625, 0.443359375, -11.3125, 1.46875]
model.layers.25.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [7.34375, 4.03125, 3.921875, 5.90625, 7.5625]
model.layers.25.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-1.3125, 0.703125, 1.703125, -2.34375, -1.3828125]
model.layers.25.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [-3.453125, 0.8984375, -4.375, -4.84375, -9.8125]
model.layers.25.post_attention_layernorm.weight torch.Size([2560])         2560      [1.4609375, 1.5078125, 1.4296875, 1.53125, 1.390625]
model.layers.25.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [6.6875, 5.71875, 7.28125, 7.21875, 8.5625]
model.layers.25.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [-1.15625, -1.171875, -3.75, 1.328125, 1.1796875]
model.layers.25.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [-1.0390625, 1.4140625, 1.359375, -2.40625, 1.0390625]
model.layers.25.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [-1.1015625, -1.59375, 0.75390625, 0.64453125, -0.12890625]
model.layers.25.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [-1.671875, -1.6875, -4.15625, -3.09375, -1.6796875]
model.layers.26.input_layernorm.weight          torch.Size([2560])         2560      [0.0150146484375, 0.013916015625, 0.01544189453125, 0.015625, 0.01556396484375]
model.layers.26.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [-3.65625, 1.3671875, 0.76953125, -2.234375, 1.2265625]
model.layers.26.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [5.46875, 11.3125, 9.125, 6.78125, 7.0]
model.layers.26.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [1.109375, -0.55078125, 3.875, -1.203125, 4.125]
model.layers.26.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [2.453125, -4.65625, 0.185546875, 1.1875, 0.056396484375]
model.layers.26.post_attention_layernorm.weight torch.Size([2560])         2560      [1.453125, 1.4453125, 1.453125, 1.546875, 1.453125]
model.layers.26.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [9.6875, 9.0, 9.0, 9.125, 9.5]
model.layers.26.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [0.5234375, -1.265625, -1.0859375, 1.390625, -1.21875]
model.layers.26.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [0.88671875, 8.375, -1.421875, 3.5625, -4.875]
model.layers.26.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [0.37890625, -0.8203125, -0.7890625, 0.66015625, 1.21875]
model.layers.26.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [9.625, 1.625, 17.875, 1.7421875, -1.4921875]
model.layers.27.input_layernorm.weight          torch.Size([2560])         2560      [0.015869140625, 0.01556396484375, 0.0169677734375, 0.017578125, 0.0167236328125]
model.layers.27.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [13.625, -0.0115966796875, 0.349609375, -1.40625, -1.2109375]
model.layers.27.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [8.875, 7.375, 8.375, 2.765625, 3.78125]
model.layers.27.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-1.2578125, 1.265625, -0.78125, -1.234375, 1.640625]
model.layers.27.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [2.109375, 3.375, 1.09375, 3.25, -6.09375]
model.layers.27.post_attention_layernorm.weight torch.Size([2560])         2560      [1.5390625, 1.5390625, 1.5234375, 1.609375, 1.5078125]
model.layers.27.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [9.9375, 9.8125, 10.375, 10.1875, 10.125]
model.layers.27.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [-1.2734375, -1.296875, -1.2890625, 3.71875, -0.9921875]
model.layers.27.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [-0.74609375, 5.46875, 1.328125, -3.65625, -0.90234375]
model.layers.27.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [-0.7890625, 0.203125, 0.205078125, 0.55078125, 0.76953125]
model.layers.27.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [1.8515625, 1.859375, -1.953125, 4.25, 1.28125]
model.layers.28.input_layernorm.weight          torch.Size([2560])         2560      [0.021240234375, 0.01556396484375, 0.0181884765625, 0.0206298828125, 0.0194091796875]
model.layers.28.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [2.015625, -1.4140625, 5.84375, 1.2890625, -0.455078125]
model.layers.28.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [4.0, 12.25, 12.0625, 10.4375, 4.4375]
model.layers.28.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-1.3359375, -9.8125, -0.94921875, 1.6015625, -0.88671875]
model.layers.28.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [-5.375, -10.8125, -4.15625, 5.4375, -1.9140625]
model.layers.28.post_attention_layernorm.weight torch.Size([2560])         2560      [1.5390625, 1.515625, 1.484375, 1.5234375, 1.484375]
model.layers.28.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [11.6875, 7.625, 13.0, 11.375, 11.4375]
model.layers.28.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [0.3359375, 1.03125, -0.57421875, -0.765625, 1.265625]
model.layers.28.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [2.140625, 3.1875, 0.9296875, -0.92578125, 0.6953125]
model.layers.28.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [-0.470703125, 0.6171875, 0.609375, 2.546875, -0.376953125]
model.layers.28.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [4.5, 1.5078125, -4.21875, 5.21875, -2.8125]
model.layers.29.input_layernorm.weight          torch.Size([2560])         2560      [0.0233154296875, 0.02490234375, 0.0216064453125, 0.0186767578125, 0.021728515625]
model.layers.29.mlp.down_proj.weight            torch.Size([2560, 6912])   17694720  [8.8125, -1.140625, 1.015625, -1.3984375, -2.96875]
model.layers.29.mlp.ffn_sub_norm.weight         torch.Size([6912])         6912      [13.875, 12.25, 4.5625, 6.84375, 17.25]
model.layers.29.mlp.gate_proj.weight            torch.Size([6912, 2560])   17694720  [-1.1171875, -0.92578125, 2.90625, 1.3359375, 1.2109375]
model.layers.29.mlp.up_proj.weight              torch.Size([6912, 2560])   17694720  [1.4609375, 7.75, 0.357421875, -1.3203125, -0.99609375]
model.layers.29.post_attention_layernorm.weight torch.Size([2560])         2560      [1.265625, 1.3125, 1.2578125, 1.1015625, 1.28125]
model.layers.29.self_attn.attn_sub_norm.weight  torch.Size([2560])         2560      [-14.0, 13.0, 11.0625, 12.1875, -7.869675755500793e-08]
model.layers.29.self_attn.k_proj.weight         torch.Size([640, 2560])    1638400   [0.384765625, -0.470703125, -4.125, 1.0625, -0.359375]
model.layers.29.self_attn.o_proj.weight         torch.Size([2560, 2560])   6553600   [0.49609375, -1.6796875, -1.59375, -0.173828125, 5.401670932769775e-07]
model.layers.29.self_attn.q_proj.weight         torch.Size([2560, 2560])   6553600   [0.57421875, -1.125, 0.5234375, -0.5703125, 0.74609375]
model.layers.29.self_attn.v_proj.weight         torch.Size([640, 2560])    1638400   [-1.1484375, -1.15625, 4.25, 0.416015625, -1.28125]
model.norm.weight                               torch.Size([2560])         2560      [0.10302734375, 0.1005859375, 0.10205078125, 0.16015625, 0.09228515625]

Todo

Test inputs against inference weights
Test official training weights for 2.4B model
- Support for other LLaMa sizes too
Make fast
- Binary kernels (triton?):
  - ternary weight matrix–vector product into two binary matmuls plus a subtraction
  - Custom XNOR–popcount routines replace expensive MAC units, enabling 10× throughput improvements in CPU binary matmul kernels
Test performance against huggingface and Microsoft bitnet.cpp
Set up custom installation script thats nice and says jax or torch and which models to run
Make new hardware for it (fpga)
Make 1-bit Mixture-of-Experts (MoE)
bitnet.c

Name		Name	Last commit message	Last commit date
Latest commit History 106 Commits
.github/workflows		.github/workflows
bitnet		bitnet
data		data
tests		tests
.gitignore		.gitignore
README.md		README.md
SPEC.md		SPEC.md
bitnet_wikitext2_1_9500.pt		bitnet_wikitext2_1_9500.pt
layer_shapes.txt		layer_shapes.txt
setup.sh		setup.sh

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