Instructions to use Exscientia/IgBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Exscientia/IgBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Exscientia/IgBert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Exscientia/IgBert") model = AutoModelForMaskedLM.from_pretrained("Exscientia/IgBert") - Notebooks
- Google Colab
- Kaggle
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README.md
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Model pretrained on protein and antibody sequences using a masked language modeling (MLM) objective. It was introduced in the paper [Large scale paired antibody language models](https://arxiv.org/abs/2403.17889).
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The model is finetuned from
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# Use
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Model pretrained on protein and antibody sequences using a masked language modeling (MLM) objective. It was introduced in the paper [Large scale paired antibody language models](https://arxiv.org/abs/2403.17889).
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The model is finetuned from IgBert-unpaired using paired antibody sequences from the [Observed Antibody Space](https://opig.stats.ox.ac.uk/webapps/oas/).
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# Use
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