Token Classification
Transformers
Safetensors
big_bird
fill-mask
CodonTransformer
Computational Biology
Machine Learning
Bioinformatics
Synthetic Biology
biology
Instructions to use adibvafa/CodonTransformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adibvafa/CodonTransformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="adibvafa/CodonTransformer")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("adibvafa/CodonTransformer") model = AutoModelForMaskedLM.from_pretrained("adibvafa/CodonTransformer") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd0e943326ef598f1db62a2a857a9968dba928ba8668a12374cfbd9b26fffdb5
- Size of remote file:
- 358 MB
- SHA256:
- 23994e1e7324e78c9d9da71040e8677c0a635287cf1c7c9ea5096b7eadc44dfd
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