Instructions to use Shadman-Rohan/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shadman-Rohan/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shadman-Rohan/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shadman-Rohan/results") model = AutoModelForSequenceClassification.from_pretrained("Shadman-Rohan/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a097840488cf5e0ffefc5e37dc3ce064ab03b5365a90dd899f3aab0754f8893a
- Size of remote file:
- 268 MB
- SHA256:
- 77c96512b6330417de68ffbdaaa8792147adcf6e831b8b680570455b03a7b510
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