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:
- 2e43a8c81d7d71dcfbd58825ba21bea3c6a58a8bde8dd75c93bb57766f51c84d
- Size of remote file:
- 428 MB
- SHA256:
- c6d1059af50788d7e1cf263a8cf1b553bc55716ae9b89afddabd6abf7cd5dd5b
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