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
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4172b3f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | 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()
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