Training w/ 13,55%

README.md

@@ -30,7 +30,7 @@ base_model:
 
 <h1 align="center">Qwen2.5-Coder-0.5B-Instruct-Gensyn-Swarm Agent-ID (tall_tame_panther)</h1>
 
-<h2 align="center">Gensyn RL-Swarm: Training & GGUF Inference for Quantized LLMs</h2>
+<h2 align="center">Gensyn RL-Swarm: Training & GGUF Quantized LLMs for Inference</h2>
 
 <p align="center">
 <a href="https://huggingface.co/0xgr3y/Qwen2.5-Coder-0.5B-Instruct-Gensyn-Swarm-tall_tame_panther"><img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Model-blue" alt="Model"></a>
@@ -41,16 +41,22 @@ base_model:
 <a href="https://github.com/gensyn-ai/rl-swarm/blob/main/LICENSE.TXT"><img src="https://img.shields.io/badge/License-MIT-green" alt="License"></a>
 </p>
 
+<div align="center">
+
+[![Gensyn](https://img.shields.io/badge/Powered%20by-Gensyn%20AI-pink?style=for-the-badge)](https://gensyn.ai)
+
+</div>
+
 ---
 
 ## Model Overview
 
-Our pick an experimental (advanced) mode at this model a continuously trained **Qwen2.5-Coder-0.5B-Instruct** fine-tuned using **Gensyn RL-Swarm** framework with **GRPO (Group Relative Policy Optimization)** and supported format **GGUF (llama.cpp)** for enhanced code generation capabilities. **Note: Current training focuses on programming challenges with adaptive weighted sampling**.
+Our pick an **experimental (advanced) mode** at this model a continuously trained `Qwen2.5-Coder-0.5B-Instruct` fine-tuned using **Gensyn RL-Swarm** framework with **GRPO (Group Relative Policy Optimization)** and supported format **GGUF (llama.cpp)** for enhanced code generation capabilities. **Note: Current training focuses on programming challenges with adaptive weighted sampling**.
 
 - **Agent ID:** `tall_tame_panther`
 - **Training Status:** 🟢 LIVE - Model updates automatically every 5-10 minutes
 - **Auto-Sync GGUF Pipeline Status:** 🟢 LIVE - Commits update automatically every hour
-- **Current Progress:** Round 13,054+ / 100,000 (13.05%)
+- **Current Progress:** Round 13,533+ / 100,000 (13.53%)
 - **Framework Version:** Gensyn RL-Swarm v0.7.0
 - **Contract:** SwarmCoordinator v0.4.2
 
@@ -59,7 +65,7 @@ Our pick an experimental (advanced) mode at this model a continuously trained **
 - **Real-time Training**: Continuous learning with distributed RL across Gensyn swarm network
 - **Adaptive System**: Dynamic quality enhanced and dataset weighting for optimal learning
 - **Multi-domain Coding**: Trained on MBPP and CodeContests datasets with adaptive sampling
-- **GGUF Support**: Multiple quantized formats available (F16, Q3_K_M, Q4_K_M, Q5_K_M)
+- **GGUF Support**: Multiple quantized formats available (F16, Q3_K_M, Q4_K_M, Q5_K_M, Q6_K)
 - **llama.cpp Compatible**: Ready for edge deployment and local inference
 - **BF16 Precision**: Trained with bfloat16 for optimal performance
 - **TGI Compatible**: Supports Text Generation Inference for production deployment
@@ -219,17 +225,19 @@ ollama create qwen2.5-coder-swarm -f Modelfile
 ollama run qwen2.5-coder-swarm "Write a function to calculate the factorial of a number."
 ```
 
-## Available Quantization Formats
+## Available GGUF Quantization
 
 | Format | Size | Precision | Use Case | Download |
 |--------|------|-----------|----------|----------|
 | Safetensors (BF16) | 988 MB | BF16 | Full precision training/fine-tuning | `model.safetensors` |
 | GGUF F16 | 994 MB | FP16 | High quality inference | `Qwen2.5-Coder-0.5B-F16.gguf` |
+| GGUF Q6_K | 506 MB | 6-bit | High quality compression | `Qwen2.5-Coder-0.5B-Q6_K.gguf` |
 | GGUF Q5_K_M | 420 MB | 5-bit | Balanced quality/size | `Qwen2.5-Coder-0.5B-Q5_K_M.gguf` |
 | GGUF Q4_K_M | 398 MB | 4-bit | **Recommended** for production | `Qwen2.5-Coder-0.5B-Q4_K_M.gguf` |
 | GGUF Q3_K_M | 355 MB | 3-bit | Smallest, fastest | `Qwen2.5-Coder-0.5B-Q3_K_M.gguf` |
 
-All GGUF formats are **llama.cpp compatible** and auto-updated hourly.
+> All GGUF formats are **llama.cpp is compatible** ready to use **Inferences chat** and auto-update be hourly.
+
 
 ## Chat Format & Conversational
 
@@ -386,8 +394,8 @@ Check commit history for exact timestamps.
 
 | Metric | Value | Target |
 |--------|-------|--------|
-| Completed Rounds | 13,054+ | 100,000 |
-| Training Progress | 13.05% | 100% |
+| Completed Rounds | 13,533+ | 100,000 |
+| Training Progress | 13.53% | 100% |
 | Update Frequency | 5-10 min | Continuous |
 
 **Note**: **average\@k:** Average performance across `k` attempts, measuring consistency. **pass\@k:** Probability of at least one correct solution in `k` attempts, measuring capability.Current metrics track training rounds completed in decentralized swarm.
@@ -463,7 +471,7 @@ git checkout <commit-hash>
 
 <div align="center">
 
-**🤖 Trained with ❤️ using Gensyn RL-Swarm**
+**Trained with 🩷 using Gensyn RL-Swarm**
 
 [![Gensyn](https://img.shields.io/badge/Powered%20by-Gensyn%20AI-pink?style=for-the-badge)](https://gensyn.ai)