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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7cf9508ad7ef3e662e435be83df28d46ad4b543d07efe0136455ba823246dfea
- Size of remote file:
- 4.47 MB
- SHA256:
- f005704280a03a768faebd87ba8cb662493e291eb2752897d7e55d9773c24c72
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