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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc4bcd808373604e0737a2f3f79d0cf91ea8d32046b3cc5503a50b56b755d3ff
- Size of remote file:
- 1.68 GB
- SHA256:
- 2a54a759568a45e8ae16f8e21f280b9893efa1b74f7f7dfdc55db7acafeb2ebc
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