Instructions to use sinequa/vectorizer.hazelnut with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sinequa/vectorizer.hazelnut with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sinequa/vectorizer.hazelnut") model = AutoModelForMaskedLM.from_pretrained("sinequa/vectorizer.hazelnut", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84e6ed7afbbc2bfdcfce75141f128323f1ef2d2c01021c12dc30ed93cfcef580
- Size of remote file:
- 395 kB
- SHA256:
- 6bf0496af06818c85b6d268c84aaec7913eaeb665d71f5451b50c9e9c5758b4a
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