--- 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/).