Instructions to use togethercomputer/m2-bert-80M-2k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use togethercomputer/m2-bert-80M-2k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="togethercomputer/m2-bert-80M-2k", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("togethercomputer/m2-bert-80M-2k", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c5e05b430edd0ea87107988b56c0079209fa967949cab4a3d56eee3f6ff670c
- Size of remote file:
- 985 MB
- SHA256:
- 8524693401aab571061c1b1b792aff2e8a6cc725aceed7a06ec205163abb4b9b
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