Instructions to use WiseIntelligence/multilingual-e5-small-Optimum-ONNX-Quantized-AVX2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WiseIntelligence/multilingual-e5-small-Optimum-ONNX-Quantized-AVX2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="WiseIntelligence/multilingual-e5-small-Optimum-ONNX-Quantized-AVX2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("WiseIntelligence/multilingual-e5-small-Optimum-ONNX-Quantized-AVX2") model = AutoModel.from_pretrained("WiseIntelligence/multilingual-e5-small-Optimum-ONNX-Quantized-AVX2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from WiseIntelligence/multilingual-e5-small-Optimum-ONNX-Quantized-AVX2: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/WiseIntelligence/multilingual-e5-small-Optimum-ONNX-Quantized-AVX2/resolve/main/tokenizer.json
- Command line
-
hf download hf://WiseIntelligence/multilingual-e5-small-Optimum-ONNX-Quantized-AVX2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/WiseIntelligence/multilingual-e5-small-Optimum-ONNX-Quantized-AVX2/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 9b58af6c3e8163fee08f9d02159732aac5dc33f8fcbe136a406533817d13f6b3
- Size of remote file:
- 17.1 MB
- SHA256:
- 2b3f6fc9286922cf30646a1957c81e5655f977d2204c9631b7624f21d6c641b5
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