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:
- 8fa8351e763d092999f3888900f8dcb7f240b78e5c9962c5cbb67580b876bda8
- Size of remote file:
- 33.6 MB
- SHA256:
- 6c884c76ac18bea4703bc13b6a1dedf5a158bd0599aefb0723377ebdee137aa7
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