Instructions to use Mozart-coder/BERT_winter-6_tokenized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mozart-coder/BERT_winter-6_tokenized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Mozart-coder/BERT_winter-6_tokenized")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Mozart-coder/BERT_winter-6_tokenized") model = AutoModelForMaskedLM.from_pretrained("Mozart-coder/BERT_winter-6_tokenized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06f43bd56c08de8b8a720ef9c2f82067679868a119f6b0a5df6a08506497e8d3
- Size of remote file:
- 357 MB
- SHA256:
- c3355dd1f902783b32c570191d06ba98c9e736f74241cf4713ac9ce62f746602
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