Instructions to use onlplab/alephbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use onlplab/alephbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="onlplab/alephbert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("onlplab/alephbert-base") model = AutoModelForMaskedLM.from_pretrained("onlplab/alephbert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): b5ed677
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 sha256:871f8c6c2a25e331d284b9787def5cf354802f0fea1d1677a712ebc672c8926c
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size 504127715
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