Instructions to use btk/output_bert_uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use btk/output_bert_uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="btk/output_bert_uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("btk/output_bert_uncased") model = AutoModelForMaskedLM.from_pretrained("btk/output_bert_uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update training_args.bin
Browse files- training_args.bin +3 -0
training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:b0bc019e71b4d58cd6f6acae256187b28e5ae3f9c12f054804f37c1f7ceb38df
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size 1035
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