Instructions to use NaturalAntibody/human_heavy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NaturalAntibody/human_heavy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NaturalAntibody/human_heavy")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NaturalAntibody/human_heavy") model = AutoModelForMaskedLM.from_pretrained("NaturalAntibody/human_heavy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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license: cc-by-nc-sa-4.0
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license: cc-by-nc-sa-4.0
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tags:
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- biology
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widget:
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- text: >-
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EV<mask>LVESGGGLVQPGGSLRLSCAASGFTFSSYNMNWVRQAPGKGLEWVSYISSSSSTIYYADSVKGRFTISRDNAKNSLSLQMNSLRDEDTAVYYCARAYYYGMDVWGQGTTVTVSS
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# Model Card for heavy human transformer
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The model is a heavy sequence specfic transformer to predict amino acids in a given position in a query sequence.
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The model was trained on sequences:
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Example usage: [notebook](example.ipynb).
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For more information please contact: contact@naturalantibody.com
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