Feature Extraction
Transformers
Safetensors
protenrich
proteins
bioinformatics
drug-discovery
custom_code
Instructions to use SaeedLab/ProtEnrich-Ankh3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaeedLab/ProtEnrich-Ankh3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SaeedLab/ProtEnrich-Ankh3", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SaeedLab/ProtEnrich-Ankh3", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Parent(s): 530a6a6
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README.md
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Use the code below to get started with the model for embedding extraction:
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```python
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from transformers import
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import torch
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tokenizer = T5Tokenizer.from_pretrained("ElnaggarLab/ankh3-xl")
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Use the code below to get started with the model for downstream prediction tasks:
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```python
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from transformers import
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import torch
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tokenizer = T5Tokenizer.from_pretrained("ElnaggarLab/ankh3-xl")
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Use the code below to get started with the model for embedding extraction:
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```python
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from transformers import AutoModel, T5EncoderModel, T5Tokenizer
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import torch
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tokenizer = T5Tokenizer.from_pretrained("ElnaggarLab/ankh3-xl")
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Use the code below to get started with the model for downstream prediction tasks:
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```python
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from transformers import AutoModelForSequenceClassification, T5EncoderModel, T5Tokenizer, AutoConfig
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import torch
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tokenizer = T5Tokenizer.from_pretrained("ElnaggarLab/ankh3-xl")
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