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 modules.json from sinequa/vectorizer.vanilla: direct link, hf CLI and curl.
- Browser
- Download file 368 Bytes
-
https://huggingface.co/sinequa/vectorizer.vanilla/resolve/refs%2Fpr%2F1/modules.json
- Command line
-
hf download hf://sinequa/vectorizer.vanilla@refs/pr/1/modules.json
-
curl -L -o modules.json https://huggingface.co/sinequa/vectorizer.vanilla/resolve/refs%2Fpr%2F1/modules.json
368 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Normalize", | |
| "type": "sentence_transformers.models.Normalize" | |
| } | |
| ] |