Instructions to use yarongef/DistilProtBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yarongef/DistilProtBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="yarongef/DistilProtBert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("yarongef/DistilProtBert") model = AutoModelForMaskedLM.from_pretrained("yarongef/DistilProtBert") - Notebooks
- Google Colab
- Kaggle
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- protein language model
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datasets:
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- Uniref50
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- protein language model
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datasets:
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- Uniref50
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# DistilProtBert model
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Pretrained model on protein sequences using a masked language modeling (MLM) objective. It was introduced in
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[this paper]() and first released in
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[this repository](). This model is trained on uppercase amino acids: it only works with capital letter amino acids.
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