Instructions to use softcatala/julibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use softcatala/julibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="softcatala/julibert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("softcatala/julibert") model = AutoModelForMaskedLM.from_pretrained("softcatala/julibert") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 5c4bd38
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:779dad664aad5a2485723f0140fc4c2f3e74c6ef7f9ee3e6cd69ff4aa5dbe54f
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size 498796983
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