Instructions to use Mozart-coder/BERT_Feb-6_tokenized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mozart-coder/BERT_Feb-6_tokenized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Mozart-coder/BERT_Feb-6_tokenized")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Mozart-coder/BERT_Feb-6_tokenized") model = AutoModelForMaskedLM.from_pretrained("Mozart-coder/BERT_Feb-6_tokenized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ec15d956b3e789372bc98462c042120e3da321e34edf911aae255389c2962ec
- Size of remote file:
- 357 MB
- SHA256:
- 4307bb6d257e92214e02d0e4af2700aa36275ab79b3db1e827c7af6e2d317d25
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