Instructions to use jeniya/BERTOverflow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jeniya/BERTOverflow with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jeniya/BERTOverflow")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jeniya/BERTOverflow") model = AutoModel.from_pretrained("jeniya/BERTOverflow", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
0361ca9
1
Parent(s): 228d6db
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:dc67d2f8840da02cb96107344eb8f1b974e02cf0b311d4c6a25ce3688baae781
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size 596076527
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