Token Classification
Transformers
Safetensors
big_bird
fill-mask
CodonTransformer
Computational Biology
Machine Learning
Bioinformatics
Synthetic Biology
Instructions to use adibvafa/CodonTransformer-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adibvafa/CodonTransformer-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="adibvafa/CodonTransformer-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("adibvafa/CodonTransformer-base") model = AutoModelForMaskedLM.from_pretrained("adibvafa/CodonTransformer-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a501e744afa90a305160fe80857731f0e112e0ec536ef6df7ffa67aebba9eb0
- Size of remote file:
- 358 MB
- SHA256:
- 3bb904b52a69cbe735962852dc5586dbe7fc71b707cd6c74efed31e1ad8de687
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