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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/).
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