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:
- 0ddc878ee9c1ec1c9d249c690e6c2bf961695a3980436020c88ef622496ae243
- Size of remote file:
- 3.38 kB
- SHA256:
- 5c7e472456305cbfdda4c1f31671bbc1d87b0b7d2def6f78ac2a9d3705d95770
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