Instructions to use hf-internal-testing/tiny-random-PersimmonForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PersimmonForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-PersimmonForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PersimmonForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-PersimmonForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 611c9c5531a9134bf23bb55cd01545f935bd637197b975d2e6e112a65183636e
- Size of remote file:
- 33.6 MB
- SHA256:
- 5a102a484ed86e6a4fc39de6f778e340c07d3c1b794f4225516fc1c1e492221f
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