Sentence Similarity
Transformers
PyTorch
xlm-roberta
feature-extraction
e5
int8
text-embeddings-inference
Instructions to use efederici/e5-multilingual-base-int8-dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use efederici/e5-multilingual-base-int8-dynamic with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("efederici/e5-multilingual-base-int8-dynamic") model = AutoModel.from_pretrained("efederici/e5-multilingual-base-int8-dynamic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a3ab999462ff6151761531d70f049fc864c51fc58528ae1eb5e009404e91acd
- Size of remote file:
- 282 MB
- SHA256:
- 4edccdf8e9b673067821f466545893b5c987b822a0748949068bb909b63c6771
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