Instructions to use raphaelsty/neural-cherche-sparse-embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raphaelsty/neural-cherche-sparse-embed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="raphaelsty/neural-cherche-sparse-embed")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("raphaelsty/neural-cherche-sparse-embed") model = AutoModelForMaskedLM.from_pretrained("raphaelsty/neural-cherche-sparse-embed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from raphaelsty/neural-cherche-sparse-embed: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
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https://huggingface.co/raphaelsty/neural-cherche-sparse-embed/resolve/main/tokenizer.json
- Command line
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hf download hf://raphaelsty/neural-cherche-sparse-embed/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/raphaelsty/neural-cherche-sparse-embed/resolve/main/tokenizer.json
712 kB
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