Instructions to use ekryski/granite-3.0-2b-instruct-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ekryski/granite-3.0-2b-instruct-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir granite-3.0-2b-instruct-4bit ekryski/granite-3.0-2b-instruct-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
granite-3.0-2b-instruct-4bit
4-bit affine quantization of ibm-granite/granite-3.0-2b-instruct, produced with FFAI 0.1.0's ffai convert (mlx-affine format, group_size=64).
Conversion
ffai convert ibm-granite/granite-3.0-2b-instruct --bits 4 \
--upload-repo ekryski/granite-3.0-2b-instruct-4bit
See also
- FFAI — fast Apple Silicon LLM inference.
Model.load("ekryski/granite-3.0-2b-instruct-4bit")runs this checkpoint end-to-end. - FFAI quickstart
- FFAI quantization docs
- Downloads last month
- 21
Model size
0.6B params
Tensor type
BF16
·
U32 ·
Hardware compatibility
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4-bit
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Model tree for ekryski/granite-3.0-2b-instruct-4bit
Base model
ibm-granite/granite-3.0-2b-base Finetuned
ibm-granite/granite-3.0-2b-instruct