Instructions to use hf-internal-testing/tiny-random-T5ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-T5ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-T5ForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-T5ForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-T5ForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1a8347b538c44abde00a8a121d85bdcc9146a9b1e58984063df51d0f91587b1
- Size of remote file:
- 4.5 MB
- SHA256:
- 7fcb69a4d403ba2177d79f72a80fab8c9be1b3faa09e8b94fb6d4a5bbfdf937e
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