初始化项目，由ModelHub XC社区提供模型
Model: 0xgr3y/Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther Source: Original Platform
This commit is contained in:
ModelHub XC
43
.gitattributes
vendored
Normal file
43
.gitattributes
vendored
Normal file
@@ -0,0 +1,43 @@
|
|||||||
|
*.7z filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.arrow filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.bin filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.bz2 filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.ckpt filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.ftz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.gz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.h5 filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.joblib filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.lfs.* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.mlmodel filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.model filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.npy filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.npz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.onnx filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.ot filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.parquet filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pb filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pickle filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pkl filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pt filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pth filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.rar filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
||||||
|
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tar filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tflite filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tgz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.wasm filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.xz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.zip filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.zst filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
Qwen3-0.6B-Gensyn-Swarm-F16.gguf filter=lfs diff=lfs merge=lfs -text
|
||||||
|
Qwen3-0.6B-Gensyn-Swarm-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
|
||||||
|
Qwen3-0.6B-Gensyn-Swarm-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
|
||||||
|
Qwen3-0.6B-Gensyn-Swarm-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
|
||||||
|
Qwen3-0.6B-F16.gguf filter=lfs diff=lfs merge=lfs -text
|
||||||
|
Qwen3-0.6B-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
|
||||||
|
Qwen3-0.6B-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
|
||||||
|
Qwen3-0.6B-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
|
||||||
3
Qwen3-0.6B-F16.gguf
Normal file
3
Qwen3-0.6B-F16.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:781945b18abb88574af9274fe71ad35c034868eee5bcfd7ec87874b7ae0074f0
|
||||||
|
size 1198182016
|
||||||
3
Qwen3-0.6B-Q3_K_M.gguf
Normal file
3
Qwen3-0.6B-Q3_K_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:f065c6970cefdefc61da4579e04607262bed1f4161017a018a09330b5b8b36a1
|
||||||
|
size 347126400
|
||||||
3
Qwen3-0.6B-Q4_K_M.gguf
Normal file
3
Qwen3-0.6B-Q4_K_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:80208a4a1629d2f64870c156281b50948cbd30ae690f5f1026b103728872ce41
|
||||||
|
size 396704384
|
||||||
3
Qwen3-0.6B-Q5_K_M.gguf
Normal file
3
Qwen3-0.6B-Q5_K_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:078da2b850fc45f77a9dba7bfa117bc19e0b41bd9a7d6c4df157be0d29fbff3f
|
||||||
|
size 444414592
|
||||||
480
README.md
Normal file
480
README.md
Normal file
@@ -0,0 +1,480 @@
|
|||||||
|
---
|
||||||
|
library_name: transformers
|
||||||
|
tags:
|
||||||
|
- text-generation
|
||||||
|
- qwen3
|
||||||
|
- rl-swarm
|
||||||
|
- genrl-swarm
|
||||||
|
- grpo
|
||||||
|
- gensyn
|
||||||
|
- trl
|
||||||
|
- reasoning
|
||||||
|
- math
|
||||||
|
- logic
|
||||||
|
- continuous-training
|
||||||
|
- reinforcement-learning
|
||||||
|
- safetensors
|
||||||
|
- gguf
|
||||||
|
- conversational
|
||||||
|
- text-generation-inference
|
||||||
|
- I am tall_tame_panther
|
||||||
|
pipeline_tag: text-generation
|
||||||
|
license: apache-2.0
|
||||||
|
language:
|
||||||
|
- en
|
||||||
|
base_model: Qwen/Qwen3-0.6B
|
||||||
|
datasets:
|
||||||
|
- propositional_logic
|
||||||
|
- calendar_arithmetic
|
||||||
|
- decimal_arithmetic
|
||||||
|
- base_conversion
|
||||||
|
- fraction_simplification
|
||||||
|
- basic_arithmetic
|
||||||
|
inference: true
|
||||||
|
widget:
|
||||||
|
- text: What is 15 * 23?
|
||||||
|
example_title: Basic Arithmetic
|
||||||
|
- text: Convert decimal 255 to hexadecimal.
|
||||||
|
example_title: Base Conversion
|
||||||
|
- text: Simplify the fraction 24/36.
|
||||||
|
example_title: Fraction Simplification
|
||||||
|
model-index:
|
||||||
|
- name: Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther
|
||||||
|
results:
|
||||||
|
- task:
|
||||||
|
type: text-generation
|
||||||
|
name: Mathematical Reasoning
|
||||||
|
dataset:
|
||||||
|
name: Composite Reasoning Dataset
|
||||||
|
type: custom
|
||||||
|
metrics:
|
||||||
|
- type: training_rounds
|
||||||
|
value: 43610
|
||||||
|
name: Completed Training Rounds
|
||||||
|
- type: total_rounds
|
||||||
|
value: 100000
|
||||||
|
name: Target Rounds
|
||||||
|
- type: progress
|
||||||
|
value: 43.61
|
||||||
|
name: Training Progress (%)
|
||||||
|
---
|
||||||
|
|
||||||
|
# Qwen3-0.6B-Gensyn-Swarm the Agent-ID (tall_tame_panther)
|
||||||
|
|
||||||
|
[](https://huggingface.co/0xgr3y/Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther)
|
||||||
|
[](https://huggingface.co/0xgr3y/Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther/tree/main)
|
||||||
|
[](https://gensyn.ai)
|
||||||
|
[](https://opensource.org/licenses/Apache-2.0)
|
||||||
|
|
||||||
|
## Model Overview
|
||||||
|
|
||||||
|
This model is a continuously trained Qwen3-0.6B fine-tuned using **Gensyn RL-Swarm** framework with **GRPO (Generalized Reward Policy Optimization)** and support **GGUF (llama.cpp)** for enhanced reasoning and mathematical capabilities. **Note: Current training focuses on math & reasoning tasks**.
|
||||||
|
|
||||||
|
- **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 1h-hourly
|
||||||
|
- **Current Progress:** Round 43,610+ / 100,000 (43,61%)
|
||||||
|
- **Framework Version:** Gensyn RL-Swarm v0.6.4
|
||||||
|
- **Contract:** SwarmCoordinator v0.4.2
|
||||||
|
|
||||||
|
## Key Features
|
||||||
|
|
||||||
|
- **Real-time Training**: Continuous learning with distributed RL across Gensyn swarm network
|
||||||
|
- **Multi-domain Reasoning**: Trained on logic, mathematical problem-solving & reasoning tasks
|
||||||
|
- **GGUF Support**: Multiple quantized formats available (F16, Q3_K_M, Q4_K_M, Q5_K_M)
|
||||||
|
- **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
|
||||||
|
- **Chat Format Support**: Inherits Qwen3 chat template for conversational use
|
||||||
|
|
||||||
|
## Training Data
|
||||||
|
|
||||||
|
The model is trained on a composite dataset (1,000 samples) with weighted sampling strategy:
|
||||||
|
|
||||||
|
| Dataset | Weight | Focus Area |
|
||||||
|
|---------|--------|------------|
|
||||||
|
| Propositional Logic | 7 | Logical reasoning, truth tables, Boolean operations |
|
||||||
|
| Calendar Arithmetic | 6 | Date calculations, leap years, recurring events |
|
||||||
|
| Decimal Arithmetic | 5 | Multi-term decimal operations with precision |
|
||||||
|
| Base Conversion | 4 | Number system conversions (base 2-16) |
|
||||||
|
| Fraction Simplification | 4 | GCD/LCM, fraction reduction |
|
||||||
|
| Basic Arithmetic | 2 | Foundation operations with parentheses |
|
||||||
|
|
||||||
|
**Total Dataset Size:** 1,000 composite samples
|
||||||
|
**Training Samples per Round:** 2
|
||||||
|
**Evaluation:** Real-time via swarm coordination
|
||||||
|
|
||||||
|
## Quick Start
|
||||||
|
|
||||||
|
### Standard Transformers
|
||||||
|
|
||||||
|
```
|
||||||
|
from transformers import AutoModelForCausalLM, AutoTokenizer
|
||||||
|
|
||||||
|
model = AutoModelForCausalLM.from_pretrained(
|
||||||
|
"0xgr3y/Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther",
|
||||||
|
torch_dtype="auto",
|
||||||
|
device_map="auto"
|
||||||
|
)
|
||||||
|
tokenizer = AutoTokenizer.from_pretrained("0xgr3y/Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther")
|
||||||
|
|
||||||
|
prompt = "What is 3/4 simplified to lowest terms?"
|
||||||
|
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
|
||||||
|
outputs = model.generate(**inputs, max_length=256, temperature=0.6, top_p=0.95)
|
||||||
|
print(tokenizer.decode(outputs, skip_special_tokens=True))
|
||||||
|
```
|
||||||
|
|
||||||
|
### Chat Format (Conversational)
|
||||||
|
|
||||||
|
```
|
||||||
|
from transformers import AutoModelForCausalLM, AutoTokenizer
|
||||||
|
|
||||||
|
model = AutoModelForCausalLM.from_pretrained("0xgr3y/Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther")
|
||||||
|
tokenizer = AutoTokenizer.from_pretrained("0xgr3y/Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther")
|
||||||
|
|
||||||
|
messages = [
|
||||||
|
{"role": "system", "content": "You are a helpful math tutor."},
|
||||||
|
{"role": "user", "content": "Explain how to simplify 24/36 step by step."}
|
||||||
|
]
|
||||||
|
|
||||||
|
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
|
||||||
|
inputs = tokenizer(text, return_tensors="pt")
|
||||||
|
outputs = model.generate(**inputs, max_length=512)
|
||||||
|
print(tokenizer.decode(outputs))
|
||||||
|
```
|
||||||
|
|
||||||
|
### Text Generation Inference (TGI)
|
||||||
|
|
||||||
|
```
|
||||||
|
docker run -d --gpus all \
|
||||||
|
-p 8080:80 \
|
||||||
|
-v $PWD/data:/data \
|
||||||
|
ghcr.io/huggingface/text-generation-inference:latest \
|
||||||
|
--model-id 0xgr3y/Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther \
|
||||||
|
--max-input-length 4096 \
|
||||||
|
--max-total-tokens 8192
|
||||||
|
```
|
||||||
|
|
||||||
|
### GGUF with llama.cpp
|
||||||
|
|
||||||
|
```
|
||||||
|
# Download quantized model (recommended: Q4_K_M)
|
||||||
|
wget https://huggingface.co/0xgr3y/Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther/resolve/main/Qwen3-0.6B-Gensyn-Swarm-Q4_K_M.gguf
|
||||||
|
|
||||||
|
# Run inference
|
||||||
|
./llama-cli -m Qwen3-0.6B-Gensyn-Swarm-Q4_K_M.gguf \
|
||||||
|
-p "Solve: (5 + 3) * 2 = ?" \
|
||||||
|
--temp 0.6 --top-p 0.95
|
||||||
|
```
|
||||||
|
|
||||||
|
### Ollama
|
||||||
|
|
||||||
|
```
|
||||||
|
# Create Modelfile
|
||||||
|
cat > Modelfile << 'EOF'
|
||||||
|
FROM ./Qwen3-0.6B-Gensyn-Swarm-Q4_K_M.gguf
|
||||||
|
PARAMETER temperature 0.6
|
||||||
|
PARAMETER top_p 0.95
|
||||||
|
PARAMETER top_k 20
|
||||||
|
SYSTEM "You are a helpful assistant specialized in mathematical reasoning and logic."
|
||||||
|
EOF
|
||||||
|
|
||||||
|
# Create and run
|
||||||
|
ollama create qwen3-swarm -f Modelfile
|
||||||
|
ollama run qwen3-swarm "What is 15 multiplied by 23?"
|
||||||
|
```
|
||||||
|
|
||||||
|
## Available Formats
|
||||||
|
|
||||||
|
| Format | Size | Precision | Use Case | Download |
|
||||||
|
|--------|------|-----------|----------|----------|
|
||||||
|
| Safetensors (BF16) | 1.19 GB | BF16 | Full precision training/fine-tuning | `model.safetensors` |
|
||||||
|
| GGUF F16 | 1.14 GB | FP16 | High quality inference | `Qwen3-0.6B-Gensyn-Swarm-F16.gguf` |
|
||||||
|
| GGUF Q5_K_M | 444 MB | 5-bit | Balanced quality/size | `Qwen3-0.6B-Gensyn-Swarm-Q5_K_M.gguf` |
|
||||||
|
| GGUF Q4_K_M | 397 MB | 4-bit | **Recommended** for production | `Qwen3-0.6B-Gensyn-Swarm-Q4_K_M.gguf` |
|
||||||
|
| GGUF Q3_K_M | 347 MB | 3-bit | Smallest, fastest | `Qwen3-0.6B-Gensyn-Swarm-Q3_K_M.gguf` |
|
||||||
|
|
||||||
|
All GGUF formats are **llama.cpp compatible** and auto-updated hourly.
|
||||||
|
|
||||||
|
### GGUF Quantization Strategy
|
||||||
|
|
||||||
|
The Q5_K_M format uses mixed precision for optimal quality:
|
||||||
|
|
||||||
|
- **Token Embeddings**: Q6_K (high quality vocab representation)
|
||||||
|
- **Attention Weights**: Q5_K (balanced quality/size)
|
||||||
|
- **Feed-Forward**: Q5_K/Q6_K (mixed for optimal performance)
|
||||||
|
- **Layer Norms**: F32 (full precision for stability)
|
||||||
|
|
||||||
|
This strategy ensures minimal quality loss while maintaining small file size.
|
||||||
|
|
||||||
|
## Chat Format & Conversational Use
|
||||||
|
|
||||||
|
This model inherits **Qwen3's chat template** for structured conversations.
|
||||||
|
|
||||||
|
### Format Structure
|
||||||
|
|
||||||
|
```
|
||||||
|
<|im_start|>system
|
||||||
|
{system_message}
|
||||||
|
<|im_end|>
|
||||||
|
<|im_start|>user
|
||||||
|
{user_message}
|
||||||
|
<|im_end|>
|
||||||
|
<|im_start|>assistant
|
||||||
|
{assistant_response}
|
||||||
|
<|im_end|>
|
||||||
|
```
|
||||||
|
|
||||||
|
### Chat Template Features
|
||||||
|
|
||||||
|
- **System Instructions**: Guide model behavior with system messages
|
||||||
|
- **Multi-turn Dialogue**: Maintains conversation context
|
||||||
|
- **Tool Calling**: Support function calling (if enabled in training)
|
||||||
|
- **Reasoning Mode**: `<think>` tags for chain-of-thought (experimental)
|
||||||
|
|
||||||
|
**Note**: While the model supports chat format structurally, optimal conversational performance depends on whether training data included formatted dialogues. Current training focuses on **math/reasoning tasks**.
|
||||||
|
|
||||||
|
## Training Configuration
|
||||||
|
|
||||||
|
### Gensyn RL-Swarm Architecture
|
||||||
|
|
||||||
|
```
|
||||||
|
Training Framework:
|
||||||
|
Method: GRPO (Generalized Reward Policy Optimization)
|
||||||
|
Base Model: Qwen/Qwen3-0.6B
|
||||||
|
Training Regime: bfloat16 mixed precision
|
||||||
|
Max Rounds: 100,000
|
||||||
|
Update Frequency: Every 5-10 minutes
|
||||||
|
Generations per Round: 2
|
||||||
|
Seed: 42
|
||||||
|
|
||||||
|
Blockchain Integration:
|
||||||
|
Network: Gensyn Testnet
|
||||||
|
Chain ID: 685685
|
||||||
|
Contract: SwarmCoordinator v0.4.2
|
||||||
|
|
||||||
|
Swarm Communication:
|
||||||
|
Framework: Hivemind P2P Backend
|
||||||
|
Initial Peers: 3 bootnodes
|
||||||
|
Beam Size: 30
|
||||||
|
|
||||||
|
Reward System:
|
||||||
|
Manager: DefaultRewardManager
|
||||||
|
Reward Function: RGRewards (Reasoning Gym)
|
||||||
|
Judge API: https://swarm-judge.internal-apps-central1.clusters.gensyn.ai
|
||||||
|
```
|
||||||
|
|
||||||
|
### Model Hyperparameters
|
||||||
|
|
||||||
|
```
|
||||||
|
Architecture:
|
||||||
|
Hidden Size: 1024
|
||||||
|
Intermediate Size: 3072
|
||||||
|
Layers: 28
|
||||||
|
Attention Heads: 16
|
||||||
|
KV Heads: 8
|
||||||
|
Head Dimension: 128
|
||||||
|
Context Length: 40,960 tokens
|
||||||
|
Vocabulary: 151,936 tokens
|
||||||
|
|
||||||
|
GRPO Config:
|
||||||
|
Epsilon: 0.2
|
||||||
|
Epsilon High: 0.28
|
||||||
|
Gradient Checkpointing: Enabled
|
||||||
|
|
||||||
|
Generation:
|
||||||
|
Temperature: 0.6
|
||||||
|
Top-K: 20
|
||||||
|
Top-P: 0.95
|
||||||
|
```
|
||||||
|
|
||||||
|
## Model Capabilities
|
||||||
|
|
||||||
|
This model excels at:
|
||||||
|
|
||||||
|
1. **Logical Reasoning**: Propositional logic, truth evaluation, Boolean algebra
|
||||||
|
2. **Mathematical Operations**: Multi-precision arithmetic, decimal calculations, fractions
|
||||||
|
3. **Number Systems**: Base conversion (binary, octal, decimal, hexadecimal)
|
||||||
|
4. **Date/Time Calculations**: Calendar arithmetic, leap years, day-of-week
|
||||||
|
5. **Step-by-step Problem Solving**: Chain-of-thought reasoning
|
||||||
|
6. **Conversational Tutoring**: Interactive problem-solving (via chat format)
|
||||||
|
|
||||||
|
## Limitations
|
||||||
|
|
||||||
|
- **Specialized Domain**: Optimized for reasoning/math; may underperform on creative writing
|
||||||
|
- **Training in Progress**: Weights update every 5-10 minutes; performance varies
|
||||||
|
- **Scale**: 0.6B parameters - suitable for edge but not SOTA for complex reasoning
|
||||||
|
- **Experimental**: Decentralized RL training; behavior less predictable than supervised models
|
||||||
|
- **Context**: Best performance within 4K tokens (full 40K supported)
|
||||||
|
|
||||||
|
## Update Schedule
|
||||||
|
|
||||||
|
| Format | Frequency | Trigger |
|
||||||
|
|--------|-----------|---------|
|
||||||
|
| Safetensors (BF16) | Every 5-10 min | Automatic via RL-Swarm |
|
||||||
|
| GGUF (all formats) | Every 1 hour | Auto-conversion pipeline |
|
||||||
|
|
||||||
|
**Auto-Conversion Pipeline:**
|
||||||
|
1. Monitors repo for new training commits
|
||||||
|
2. Downloads latest `model.safetensors`
|
||||||
|
3. Converts to F16 GGUF base
|
||||||
|
4. Quantizes to Q3_K_M, Q4_K_M, Q5_K_M
|
||||||
|
5. Uploads all formats
|
||||||
|
|
||||||
|
Check commit history for exact timestamps.
|
||||||
|
|
||||||
|
## Gensyn RL-Swarm Technical Details
|
||||||
|
|
||||||
|
### Architecture Components
|
||||||
|
|
||||||
|
1. **Game Manager**: Orchestrates training rounds and swarm coordination
|
||||||
|
2. **Trainer**: GRPO implementation for policy optimization
|
||||||
|
3. **Data Manager**: Dataset loading and weighted sampling
|
||||||
|
4. **Reward Manager**: Computes rewards via judge API
|
||||||
|
5. **Coordinator**: Blockchain integration for swarm state
|
||||||
|
6. **P2P Backend**: Hivemind DHT for model sharing
|
||||||
|
|
||||||
|
### Training Process
|
||||||
|
|
||||||
|
```
|
||||||
|
1. Agent joins swarm via P2P network
|
||||||
|
2. Coordinator assigns round via smart contract
|
||||||
|
3. Agent samples data from weighted datasets
|
||||||
|
4. Model generates 2 responses
|
||||||
|
5. Judge API evaluates and assigns rewards
|
||||||
|
6. GRPO updates policy based on rewards
|
||||||
|
7. Updated model shared via DHT
|
||||||
|
8. Best checkpoint saved to HuggingFace
|
||||||
|
9. Repeat
|
||||||
|
```
|
||||||
|
|
||||||
|
### Decentralization Benefits
|
||||||
|
|
||||||
|
- **Fault Tolerance**: Multiple agents; no single point of failure
|
||||||
|
- **Diverse Exploration**: Different agents explore different strategies
|
||||||
|
- **Collective Intelligence**: Agents learn from each other
|
||||||
|
- **Transparent**: All rounds verified on-chain
|
||||||
|
|
||||||
|
**Swarm Agent:** `tall_tame_panther`
|
||||||
|
**Contract:** SwarmCoordinator v0.4.2
|
||||||
|
|
||||||
|
## Technical Specifications
|
||||||
|
|
||||||
|
### Software Stack
|
||||||
|
|
||||||
|
- **Framework**: Gensyn RL-Swarm v0.6.4
|
||||||
|
- **Library**: transformers v4.51+
|
||||||
|
- **P2P**: hivemind
|
||||||
|
- **Blockchain**: Gensyn testnet
|
||||||
|
- **Config**: Hydra + OmegaConf
|
||||||
|
- **Logging**: WandB integration
|
||||||
|
|
||||||
|
### Hardware Requirements
|
||||||
|
|
||||||
|
**Training GPU:**
|
||||||
|
- GPU: NVIDIA 4090 24GB+ (BF16 training)
|
||||||
|
- RAM: 16GB+
|
||||||
|
- Cores: 10+
|
||||||
|
- Storage: 50GB SSD
|
||||||
|
- Network: High bandwidth for P2P
|
||||||
|
|
||||||
|
**Training CPU Optimize:**
|
||||||
|
- CPU: INTEL or AMD
|
||||||
|
- Cores: 10+
|
||||||
|
- RAM: 16GB+
|
||||||
|
- Storage: 50GB SSD
|
||||||
|
- Network: High bandwidth for P2P
|
||||||
|
|
||||||
|
**Inference:**
|
||||||
|
- Safetensors: 8GB VRAM (GPU) / 16GB RAM (CPU)
|
||||||
|
- GGUF Q4_K_M: 2GB VRAM (GPU) / 4GB RAM (CPU)
|
||||||
|
- GGUF Q3_K_M: 3GB RAM (CPU-only)
|
||||||
|
|
||||||
|
## Evaluation
|
||||||
|
|
||||||
|
### Training Progress Metrics
|
||||||
|
|
||||||
|
| Metric | Value | Target |
|
||||||
|
|--------|-------|--------|
|
||||||
|
| Completed Rounds | 43,610+ | 100,000 |
|
||||||
|
| Training Progress | 43.61% | 100% |
|
||||||
|
| Update Frequency | 5-10 min | Continuous |
|
||||||
|
|
||||||
|
**Note**: Formal evaluation benchmarks (GSM8K, MATH, etc.) will be added as training progresses. Current metrics track training rounds completed in the decentralized swarm.
|
||||||
|
|
||||||
|
## Reproducibility
|
||||||
|
|
||||||
|
To reproduce training:
|
||||||
|
|
||||||
|
1. Clone Gensyn RL-Swarm repository
|
||||||
|
2. Install: `pip install -r requirements.txt`
|
||||||
|
3. Configure `rgym_exp/config/rg-swarm.yaml`
|
||||||
|
4. Configure `rgym_exp/src/datasets.yaml`
|
||||||
|
5. Set environment variables:
|
||||||
|
```
|
||||||
|
export HUGGINGFACE_ACCESS_TOKEN=<token>
|
||||||
|
export MODEL_NAME=Qwen/Qwen3-0.6B
|
||||||
|
export ORG_ID=<org-id>
|
||||||
|
export SWARM_CONTRACT=<contract-address>
|
||||||
|
```
|
||||||
|
6. Run: `bash run_rl_swarm.sh`
|
||||||
|
|
||||||
|
**Note**: Exact reproduction requires same seed (42), dataset config, and swarm state.
|
||||||
|
|
||||||
|
## Citation
|
||||||
|
|
||||||
|
```
|
||||||
|
@misc{qwen3-gensyn-swarm-2025,
|
||||||
|
author = {0xgrey},
|
||||||
|
title = {Qwen3-0.6B-Gensyn-Swarm: Continuous RL Training on Distributed Swarm},
|
||||||
|
year = {2025},
|
||||||
|
publisher = {HuggingFace},
|
||||||
|
howpublished = {\url{https://huggingface.co/0xgr3y/Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther}},
|
||||||
|
note = {Agent ID: tall\_tame\_panther}
|
||||||
|
}
|
||||||
|
|
||||||
|
@misc{gensyn-rl-swarm-2025,
|
||||||
|
title = {Gensyn RL-Swarm: Decentralized Reinforcement Learning Framework},
|
||||||
|
author = {Gensyn AI},
|
||||||
|
year = {2025},
|
||||||
|
url = {https://gensyn.ai}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## References
|
||||||
|
|
||||||
|
- **Gensyn Documentation**: https://docs.gensyn.ai/
|
||||||
|
- **Gensyn GitHub**: https://github.com/gensyn-ai
|
||||||
|
- **RL-Swarm Contracts**: https://github.com/gensyn-ai/rl-swarm-contracts
|
||||||
|
- **Qwen3 Model Card**: https://huggingface.co/Qwen/Qwen3-0.6B
|
||||||
|
- **arXiv:1910.09700**: ML Carbon Emissions methodology
|
||||||
|
|
||||||
|
## License
|
||||||
|
|
||||||
|
Apache 2.0 - See [LICENSE](LICENSE)
|
||||||
|
|
||||||
|
## Contact
|
||||||
|
|
||||||
|
- **Developer**: 0xgrey
|
||||||
|
- **Agent ID**: tall_tame_panther
|
||||||
|
- **Community**: [Gensyn Discord](https://discord.gg/gensyn)
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
**⚠️ Important**: This is a continuously trained model. For reproducibility, specify commit hash:
|
||||||
|
|
||||||
|
```
|
||||||
|
git clone https://huggingface.co/0xgr3y/Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther
|
||||||
|
cd Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther
|
||||||
|
git checkout <commit-hash>
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
<div align="center">
|
||||||
|
|
||||||
|
**🤖 Trained with ❤️ using Gensyn RL-Swarm**
|
||||||
|
|
||||||
|
[](https://gensyn.ai)
|
||||||
|
|
||||||
|
</div>
|
||||||
30
config.json
Normal file
30
config.json
Normal file
@@ -0,0 +1,30 @@
|
|||||||
|
{
|
||||||
|
"architectures": [
|
||||||
|
"Qwen3ForCausalLM"
|
||||||
|
],
|
||||||
|
"attention_bias": false,
|
||||||
|
"attention_dropout": 0.0,
|
||||||
|
"bos_token_id": 151643,
|
||||||
|
"eos_token_id": 151645,
|
||||||
|
"head_dim": 128,
|
||||||
|
"hidden_act": "silu",
|
||||||
|
"hidden_size": 1024,
|
||||||
|
"initializer_range": 0.02,
|
||||||
|
"intermediate_size": 3072,
|
||||||
|
"max_position_embeddings": 40960,
|
||||||
|
"max_window_layers": 28,
|
||||||
|
"model_type": "qwen3",
|
||||||
|
"num_attention_heads": 16,
|
||||||
|
"num_hidden_layers": 28,
|
||||||
|
"num_key_value_heads": 8,
|
||||||
|
"rms_norm_eps": 1e-06,
|
||||||
|
"rope_scaling": null,
|
||||||
|
"rope_theta": 1000000,
|
||||||
|
"sliding_window": null,
|
||||||
|
"tie_word_embeddings": true,
|
||||||
|
"torch_dtype": "bfloat16",
|
||||||
|
"transformers_version": "4.51.3",
|
||||||
|
"use_cache": true,
|
||||||
|
"use_sliding_window": false,
|
||||||
|
"vocab_size": 151936
|
||||||
|
}
|
||||||
13
generation_config.json
Normal file
13
generation_config.json
Normal file
@@ -0,0 +1,13 @@
|
|||||||
|
{
|
||||||
|
"bos_token_id": 151643,
|
||||||
|
"do_sample": true,
|
||||||
|
"eos_token_id": [
|
||||||
|
151645,
|
||||||
|
151643
|
||||||
|
],
|
||||||
|
"pad_token_id": 151643,
|
||||||
|
"temperature": 0.6,
|
||||||
|
"top_k": 20,
|
||||||
|
"top_p": 0.95,
|
||||||
|
"transformers_version": "4.51.3"
|
||||||
|
}
|
||||||
3
model.safetensors
Normal file
3
model.safetensors
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:5dab513aba5eab584b0c2e029bd3df4a2b2ce34109af35babe9e178dd193602c
|
||||||
|
size 1192135096
|
||||||
Reference in New Issue
Block a user