Instructions to use raphaelsty/distilbert-sparsembed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raphaelsty/distilbert-sparsembed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="raphaelsty/distilbert-sparsembed", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("raphaelsty/distilbert-sparsembed") model = AutoModelForMaskedLM.from_pretrained("raphaelsty/distilbert-sparsembed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9efdcadece61fdc6649e7d6ff97fa69d31c1fe16ba9b65b731189c54b23b97c
- Size of remote file:
- 268 MB
- SHA256:
- b53b35b77aed0a3705c49c6d7d88064a4e5733de1aee4f61e64b8470fe79cc09
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