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
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README.md
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import torch
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from transformers import AutoTokenizer, BigBirdForMaskedLM
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from CodonTransformer.CodonPrediction import predict_dna_sequence
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from CodonTransformer.CodonUtils import ORGANISM2ID
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from CodonTransformer.CodonJupyter import format_model_output
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DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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import torch
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from transformers import AutoTokenizer, BigBirdForMaskedLM
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from CodonTransformer.CodonPrediction import predict_dna_sequence
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from CodonTransformer.CodonJupyter import format_model_output
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DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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