Instructions to use raphaelsty/distilbert-splade with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raphaelsty/distilbert-splade with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="raphaelsty/distilbert-splade")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("raphaelsty/distilbert-splade") model = AutoModelForMaskedLM.from_pretrained("raphaelsty/distilbert-splade") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d7e405eb3a1e9a0b015dd854c76e09f20888b937d669b4fb610aa0e533f89bd
- Size of remote file:
- 268 MB
- SHA256:
- 443c32f1146d839022ca2ca86a994098096fa71900d815f107dae7def10b8695
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