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
Adding `safetensors` variant of this model
#14
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2a54a759568a45e8ae16f8e21f280b9893efa1b74f7f7dfdc55db7acafeb2ebc
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size 1680111592
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