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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("adibvafa/CodonTransformer-base") model = AutoModelForMaskedLM.from_pretrained("adibvafa/CodonTransformer-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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# Load model and tokenizer
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tokenizer = AutoTokenizer.from_pretrained("adibvafa/CodonTransformer")
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model = BigBirdForMaskedLM.from_pretrained("adibvafa/CodonTransformer").to(DEVICE)
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# Set your input data
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# Load model and tokenizer
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tokenizer = AutoTokenizer.from_pretrained("adibvafa/CodonTransformer")
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model = BigBirdForMaskedLM.from_pretrained("adibvafa/CodonTransformer-pretrain").to(DEVICE)
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# Set your input data
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