Instructions to use typeof/all-MiniLM-L6-v2-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use typeof/all-MiniLM-L6-v2-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="typeof/all-MiniLM-L6-v2-onnx")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("typeof/all-MiniLM-L6-v2-onnx") model = AutoModel.from_pretrained("typeof/all-MiniLM-L6-v2-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_optimized_quantized.onnx from typeof/all-MiniLM-L6-v2-onnx: direct link, hf CLI and curl.
- Browser
- Download file 22.7 MB
-
https://huggingface.co/typeof/all-MiniLM-L6-v2-onnx/resolve/main/model_optimized_quantized.onnx
- Command line
-
hf download hf://typeof/all-MiniLM-L6-v2-onnx/model_optimized_quantized.onnx
-
curl -L -o model_optimized_quantized.onnx https://huggingface.co/typeof/all-MiniLM-L6-v2-onnx/resolve/main/model_optimized_quantized.onnx
22.7 MB
- Xet hash:
- 4ff612961fcdbf8bfaf382a559ca2cf26e1b320221fd0822adc3c3ad6746e596
- Size of remote file:
- 22.7 MB
- SHA256:
- 075962c35df725866da93cfe4c8f337a59e56e4fd97a30ccf1b249aa4d607f05
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