Instructions to use efederici/multilingual-e5-small-int8-dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use efederici/multilingual-e5-small-int8-dynamic with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("efederici/multilingual-e5-small-int8-dynamic") model = AutoModel.from_pretrained("efederici/multilingual-e5-small-int8-dynamic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from efederici/multilingual-e5-small-int8-dynamic: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/efederici/multilingual-e5-small-int8-dynamic/resolve/main/tokenizer.json
- Command line
-
hf download hf://efederici/multilingual-e5-small-int8-dynamic/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/efederici/multilingual-e5-small-int8-dynamic/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 1c8f7c8fd9b7c56a43be9844713bdd468b7a17ed5170311ce768adfc6e2d41ea
- Size of remote file:
- 17.1 MB
- SHA256:
- 0b44a9d7b51c3c62626640cda0e2c2f70fdacdc25bbbd68038369d14ebdf4c39
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