Instructions to use JulesBelveze/labse-bfloat16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JulesBelveze/labse-bfloat16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="JulesBelveze/labse-bfloat16")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("JulesBelveze/labse-bfloat16") model = AutoModel.from_pretrained("JulesBelveze/labse-bfloat16") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:de96c54d4b901d61da99c4b821ed380eac066f6183f7eb797fda1f1df065aba4
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size 941876272
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