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---
base_model: OctoAI/OctoThinker-3B
license: apache-2.0
language:
- en
library_name: transformers
pipeline_tag: text-generation
tags:
- spiral
- self-play
- reinforcement-learning
- octothinker
- multi-agent
---
# SPIRAL OctoThinker-3B Multi-Agent Model
This model was trained using the SPIRAL (Self-Play Iterative Reinforcement learning for Adaptation and Learning) framework.
## Model Details
- **Base Model**: OctoAI/OctoThinker-3B
- **Training Framework**: SPIRAL
- **Checkpoint**: step_00192
- **Model Size**: 3B parameters
- **Training Date**: 2025-08-26
## Training Configuration
The model was trained with self-play on multiple environments:
- KuhnPoker-v1
- TicTacToe-v0
- SimpleNegotiation-v1
### Training Parameters
```json
{
"learning_rate": "1e-6",
"train_batch_size": 128,
"num_ppo_epochs": 2,
"temperature": 1.0,
"max_model_len": 16384,
"environments": [
"KuhnPoker-v1",
"TicTacToe-v0",
"SimpleNegotiation-v1"
],
"base_model": "OctoAI/OctoThinker-3B",
"framework": "SPIRAL"
}
```
## Usage
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained("the-acorn-ai/spiral-octothinker-3b-multi-step00192")
model = AutoModelForCausalLM.from_pretrained(
"the-acorn-ai/spiral-octothinker-3b-multi-step00192",
torch_dtype=torch.bfloat16,
device_map="auto"
)
# Generate text
inputs = tokenizer("Your prompt here", return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
```
## License
This model is licensed under the Apache License 2.0.
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