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Neural Condense Subnet
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💡 Explore Our Ecosystem 💡

Component Link
🌐 Condense-AI & API Document Visit Condense-AI
📚 API Library Explore API Library
🔗 Organic Forwarder For Validators Check Organic Forwarder
📊 Miner Leaderboard & Statistics View Miner Dashboard or Wandb Logger

Changelogs

  • (25/11/2024) Version 0.0.2 Update: Added condensing activations layers, Switched to Distributed Storage from Restful API Transfer, Emissions now allocated only to the top 30% miners.

🌟 Key Features:

⚡ Subnet as an Accelerate Adapter for LLM Inference

  • 🌐 Seamless Integration: Effortlessly integrates with LLM inference engines, such as transformers 🤗, vllm.
  • 🧩 Token Compression: The subnet API compresses long sequences of natural language tokens into soft tokens.
  • 🏛️ Decentralized Network: The subnet is a decentralized network that allows miners to contribute to the compression process.
  • 📊 Tiered System: The subnet has a tiered system, with a research tier for experimentation and an inference tier for production-scale use. Incentive distribution is splitted for each tier.
  • 📏 Benchmarking and Validation: The subnet owner defines synthetic metrics to benchmark miners’ performance, ensuring quality and efficiency.
condense

⚙️ Node Tiers

Tier Purpose Context Size Incentive Percentage Supporting Models
research Optimize text-to-kv cache for a specific model Up to 15000 characters 60% mistralai/Mistral-7B-Instruct-v0.2
universal Compress text representation for various models Up to 15000 characters 40% meta-llama/Llama-3.1-8B-Instruct

Supporting models can be flexibly added based on tailored need.

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📚 Documentation

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  • Python 98.3%
  • Shell 1.7%
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