Text Classification
Transformers
PyTorch
bert
protein language model
biology
text-embeddings-inference
Instructions to use GleghornLab/SYNTERACT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GleghornLab/SYNTERACT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GleghornLab/SYNTERACT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GleghornLab/SYNTERACT") model = AutoModelForSequenceClassification.from_pretrained("GleghornLab/SYNTERACT") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -1
config.json
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{
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"_name_or_path": "
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"_num_labels": 2,
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"architectures": [
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"BertForSequenceClassification"
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"_name_or_path": "SYNTERACT",
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"_num_labels": 2,
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"architectures": [
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"BertForSequenceClassification"
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