Instructions to use roychowdhuryresearch/dna2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roychowdhuryresearch/dna2vec with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("roychowdhuryresearch/dna2vec", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -67,7 +67,7 @@ def load_hf_model():
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```python
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def get_embedding(dna_sequence):
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model, tokenizer, pooler = load_hf_model()
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tokenized_input = tokenizer(dna_sequence, return_tensors="pt")
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with torch.no_grad():
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output = model(**tokenized_input)
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embedding = pooler(output.last_hidden_state, tokenized_input.attention_mask)
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```python
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def get_embedding(dna_sequence):
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model, tokenizer, pooler = load_hf_model()
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tokenized_input = tokenizer(dna_sequence, return_tensors="pt", padding = True)
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with torch.no_grad():
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output = model(**tokenized_input)
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embedding = pooler(output.last_hidden_state, tokenized_input.attention_mask)
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