Feature Extraction
MLX
Safetensors
qwen2
embeddings
sentence-similarity
quantization
omlx
q6
6-bit
custom_code
Instructions to use TiGa-RCE/gte-Qwen2-1.5B-instruct-MLX-Q6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TiGa-RCE/gte-Qwen2-1.5B-instruct-MLX-Q6 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir gte-Qwen2-1.5B-instruct-MLX-Q6 TiGa-RCE/gte-Qwen2-1.5B-instruct-MLX-Q6
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Xet hash:
- 7a5b95162b7e9d02537ad3b506c88ee09dae7c886c1f70c8b6afbbf7ce2c456a
- Size of remote file:
- 11.4 MB
- SHA256:
- 48f722bc04c884e2fe1525fdcd85a1293a8499b6e620c1ac7c083c49632305fb
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