Instructions to use mlx-community/Llama-3.2-1B-Instruct-mlx-FinGreyLit-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Llama-3.2-1B-Instruct-mlx-FinGreyLit-finetuned with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/Llama-3.2-1B-Instruct-mlx-FinGreyLit-finetuned --local-dir Llama-3.2-1B-Instruct-mlx-FinGreyLit-finetuned
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
This is a fine-tuned model of (meta-llama/Llama-3.2-1B-Instruct)[https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct] using MLX on Apple Silicon. The dataset is based on (FinGreyLit)[https://github.com/NatLibFi/FinGreyLit], a dataset of Finnish Grey Literature. Only the English articles from the complete FinGreyLit data set were used for training.
The model is trained as a Librarian to extract bibliographic information from papers with the system prompt:
"You are a skilled librarian specialized in meticulous cataloguing of digital documents. Extract metadata from this document. Return as JSON."
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Model size
1B params
Tensor type
BF16
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meta-llama/Llama-3.2-1B-Instruct