Instructions to use WiseIntelligence/multilingual-e5-large-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-large-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-large-Optimum-ONNX-Quantized-AVX2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("WiseIntelligence/multilingual-e5-large-Optimum-ONNX-Quantized-AVX2") model = AutoModel.from_pretrained("WiseIntelligence/multilingual-e5-large-Optimum-ONNX-Quantized-AVX2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from WiseIntelligence/multilingual-e5-large-Optimum-ONNX-Quantized-AVX2: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/WiseIntelligence/multilingual-e5-large-Optimum-ONNX-Quantized-AVX2/resolve/main/tokenizer.json
- Command line
-
hf download hf://WiseIntelligence/multilingual-e5-large-Optimum-ONNX-Quantized-AVX2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/WiseIntelligence/multilingual-e5-large-Optimum-ONNX-Quantized-AVX2/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 8db672676f02cda7a7855c1866ed1feffa438813f777f149a8f1ff977c07fcd6
- Size of remote file:
- 17.1 MB
- SHA256:
- 19232daba569c004c5fbe45f373ccaf2ee505055da00969f78a99e5754db8f25
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