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
Download reduction_layer.bin from sinequa/vectorizer.vanilla: direct link, hf CLI and curl.
- Browser
- Download file 395 kB
-
https://huggingface.co/sinequa/vectorizer.vanilla/resolve/refs%2Fpr%2F1/reduction_layer.bin
- Command line
-
hf download hf://sinequa/vectorizer.vanilla@refs/pr/1/reduction_layer.bin
-
curl -L -o reduction_layer.bin https://huggingface.co/sinequa/vectorizer.vanilla/resolve/refs%2Fpr%2F1/reduction_layer.bin
395 kB
- Xet hash:
- f3f89ebe20b7adbd85bba6e19c9aff63c2d4ea2fdbf0ff01d05f1cdd95f6eb63
- Size of remote file:
- 395 kB
- SHA256:
- 289032bdeb08c247f2ab93bcea9e346577fb44a290545d19ff945788843a0340
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