Instructions to use raphaelsty/neural-cherche-colbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raphaelsty/neural-cherche-colbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="raphaelsty/neural-cherche-colbert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("raphaelsty/neural-cherche-colbert") model = AutoModelForMaskedLM.from_pretrained("raphaelsty/neural-cherche-colbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af6f9e42d198ab0c56f05e70db8478167162f442535b83c9cc6a37738e54f5c1
- Size of remote file:
- 394 kB
- SHA256:
- 51c6fe3495544322ca5339d03f91afe54f6234d441f5b69b6f062f483fc9ce99
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