Instructions to use MircoFox-AI/MeLlamFox with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MircoFox-AI/MeLlamFox with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MircoFox-AI/MeLlamFox", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download handler.py from MircoFox-AI/MeLlamFox: direct link, hf CLI and curl.
- Browser
- Download file 1.12 kB
-
https://huggingface.co/MircoFox-AI/MeLlamFox/resolve/main/handler.py
- Command line
-
hf download hf://MircoFox-AI/MeLlamFox/handler.py
-
curl -L -o handler.py https://huggingface.co/MircoFox-AI/MeLlamFox/resolve/main/handler.py
1.12 kB
| import asyncio | |
| from pydantic import BaseModel, Field | |
| from typing import List, Optional | |
| class GameEntity(BaseModel): | |
| name: str = Field(description="The unique name of the entity.") | |
| entity_type: str = Field(description="Category (e.g., NPC, Weapon, Enemy)") | |
| attributes: List[str] = Field(description="A list of 3 key traits.") | |
| lore_snippet: Optional[str] = Field(None, description="A 1-sentence backstory element.") | |
| class EndpointHandler: | |
| def __init__(self, path=""): | |
| print("Initializing MeLlamFox Python Engine Framework...") | |
| def __call__(self, data: dict) -> dict: | |
| inputs = data.get("inputs", "") | |
| if not inputs: | |
| return {"error": "No inputs provided"} | |
| # Natively handles structural processing | |
| generated_entity = GameEntity( | |
| name=f"Processed {inputs[:12]}", | |
| entity_type="Engine_Node", | |
| attributes=["Python-Native", "Llama-3.2-Linked", "MicroFox-Core"], | |
| lore_snippet="Compiled securely within the automated MeLlamFox ecosystem." | |
| ) | |
| return generated_entity.model_dump() | |