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:
- 4022c245ada7dbb62caf2aaa7509635c0079b098996339c98bc8b3a98bcd5eff
- Size of remote file:
- 4.5 MB
- SHA256:
- 8afd3766e858721eeab112600e76bbd5fc0dfdf2fbcc76e00453223cb6e4443e
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