README.md

---
language:
- en
license: mit
library_name: transformers
pipeline_tag: text-generation
tags:
- fableforge
- agent
- code-generation
- tool-use
- reasoning
- base
base_model: meta-llama/Llama-2-7b-chat-hf
---

# FableForge

The base unified agent model - a 7B parameter model fine-tuned for agent tasks including planning, tool use, code generation, and self-correction. The foundation model for the FableForge ecosystem.

## Quick Start

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "fableforge-ai/FableForge"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")

prompt = """You are an AI agent. Complete the following task:

Task: Write a Python function to calculate the Fibonacci sequence.

Reasoning:"""

inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.6, top_p=0.9)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## Use Cases

- General-purpose agent tasks
- Planning and decomposition
- Code generation with self-verification
- Integration with FableForge runtime and tools

### Integration with FableForge Ecosystem

```python
from fableforge_agent_runtime import AgentRuntime
from fableforge_agent_skills import SkillLibrary

runtime = AgentRuntime(
    model="fableforge-ai/FableForge",
    skills=SkillLibrary.all(),
    verification=True
)

result = runtime.run("Deploy a web server on AWS")
print(result.output)
print(result.verification_score)
```

## Ecosystem Integration

Part of the **FableForge Agent Ecosystem** - 21 open-source projects for building, testing, and deploying AI agents.

| Package | Install | Purpose |
|---------|---------|---------|
| `fableforge` | `pip install fableforge` | Unified CLI |
| `fableforge-anvil-agent` | `pip install fableforge-anvil-agent` | Self-verified coding agent |
| `fableforge-agent-swarm` | `pip install fableforge-agent-swarm` | Multi-agent orchestration |
| `fableforge-agent-runtime` | `pip install fableforge-agent-runtime` | Production agent runtime |
| `fableforge-agent-skills` | `pip install fableforge-agent-skills` | Skill library |
| `verifyloop` | `pip install verifyloop` | Verification loops |
| `reason-critic` | `pip install reason-critic` | Reasoning assessment |

## Model Details

| Attribute | Value |
|-----------|-------|
| Architecture | LlamaForCausalLM |
| Parameters | 7B |
| Hidden Size | 4096 |
| Layers | 32 |
| Attention Heads | 32 |
| KV Heads | 32 |
| Max Context | 4096 |
| Training Data | Fable5 agent traces + curated reasoning datasets |
| License | MIT |

## Limitations

- May generate incorrect code -- always use with verifyloop for critical tasks
- Trained primarily on English data; multilingual performance is limited
- Can hallucinate API signatures or tool parameters
- Not suitable for medical, legal, or financial advice without human review

## Citation

```bibtex
@misc{fableforge2024,
  title={FableForge: Agent Orchestration via Fine-Tuned Language Models},
  author={FableForge Team},
  year={2024},
  url={https://huggingface.co/fableforge-ai/FableForge}
}
```

## License

MIT License - see [LICENSE](LICENSE) for details.

---

Built with hammer by the [FableForge](https://github.com/KingLabsA) team. Part of the [FableForge ecosystem](https://kinglabsa.github.io/fableforge/).