Instructions to use ElnaggarLab/ankh3-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ElnaggarLab/ankh3-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ElnaggarLab/ankh3-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ElnaggarLab/ankh3-large") model = AutoModelForSeq2SeqLM.from_pretrained("ElnaggarLab/ankh3-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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The idea of this task is to cut the input sequence into
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two segments, where the first segment is fed to the encoder
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and the decoder is tasked to auto-regressively generate the
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2. Protein Sequence Completion:
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The idea of this task is to cut the input sequence into
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two segments, where the first segment is fed to the encoder
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and the decoder is tasked to auto-regressively generate the
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