Instructions to use Mozart-coder/BERT_Dec-6_tokenized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mozart-coder/BERT_Dec-6_tokenized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Mozart-coder/BERT_Dec-6_tokenized")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Mozart-coder/BERT_Dec-6_tokenized") model = AutoModelForMaskedLM.from_pretrained("Mozart-coder/BERT_Dec-6_tokenized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7b589eb168764210fb0d39e926fd1e53b1e26115b8fda6a5296df0af3175bb3
- Size of remote file:
- 357 MB
- SHA256:
- d23cef1a37f22c8dd115d45e494c4d7d48f7f53a26ae138d4f70167333945a62
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