Instructions to use Taykhoom/CodonBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taykhoom/CodonBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Taykhoom/CodonBERT", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Taykhoom/CodonBERT", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51bcf4b85a21477c2b9bccf060c22db72782d3589e017c7c133e529f35c5ecf2
- Size of remote file:
- 349 MB
- SHA256:
- 534daf559ebc571a3158fed93fe140094f39c62eee74edc7bc319f66d6d89957
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