Instructions to use sinequa/vectorizer.vanilla with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sinequa/vectorizer.vanilla with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sinequa/vectorizer.vanilla") model = AutoModel.from_pretrained("sinequa/vectorizer.vanilla", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.321e245
-
Update model card (#3)
Verified signature- Update model card (590b2b2a7925c99f773e9878c847845371f177fd)6820cbc
-
Adding scale factor
b37367d
-
Initial model card (#2)
- initial model card (23f11cd3e52db0851482186928fe92737957e205)53a1641
-
Initial commit (#1)
- initial commit (f4ca4f3f372324d60b9f319209b66c9c323f2072)ce95f31 -
initial commit
10d89e6