Text Classification
Transformers
PyTorch
rita
protein language model
Generated from Trainer
custom_code
Eval Results (legacy)
Instructions to use thundaa/tape-fluorescence-prediction-RITA_s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thundaa/tape-fluorescence-prediction-RITA_s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thundaa/tape-fluorescence-prediction-RITA_s", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("thundaa/tape-fluorescence-prediction-RITA_s", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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