Feature Extraction
Transformers
PyTorch
Safetensors
English
bert
token-classification
text-embeddings-inference
Instructions to use bioscan-ml/BarcodeBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bioscan-ml/BarcodeBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bioscan-ml/BarcodeBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bioscan-ml/BarcodeBERT") model = AutoModelForTokenClassification.from_pretrained("bioscan-ml/BarcodeBERT") - Notebooks
- Google Colab
- Kaggle
Add short model description (#4)
Browse files- Add short model description (cc0abe560369f4098ffff3217b5d2203dbcbb49f)
- Standardize description (8e1b93423b64cd28c30196b8e94a515acdc72416)
Co-authored-by: Anna Viklund <annaviklund@users.noreply.huggingface.co>
README.md
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license: mit
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pipeline_tag: feature-extraction
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library_name: transformers
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# BarcodeBERT for Taxonomic Classification
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license: mit
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pipeline_tag: feature-extraction
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library_name: transformers
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description: "Pretrained weights for BarcodeBERT, a transformer for insect DNA barcode inference."
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# BarcodeBERT for Taxonomic Classification
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