Instructions to use ndlanier/gutsignal-food-parser-tinyllama-1.1b-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ndlanier/gutsignal-food-parser-tinyllama-1.1b-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir gutsignal-food-parser-tinyllama-1.1b-mlx ndlanier/gutsignal-food-parser-tinyllama-1.1b-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 614 Bytes
5a20bab | 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 29 | {
"model_name": "GutSignal Food Parsing - gutsync_food_analysis_tinyllama-1.1b",
"version": "1.0.0",
"format": "MLX",
"framework": "Apple MLX",
"base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"license": "apache-2.0",
"description": "Fine-tuned language model for parsing food descriptions",
"target_ios_version": "18.0+",
"categories": [
"dairy",
"grains",
"protein",
"vegetables",
"fruits",
"fats",
"sugars",
"beverages",
"spicy",
"fiber",
"processed",
"caffeine",
"alcohol",
"fermented",
"nuts",
"legumes",
"unknown"
]
} |