Instructions to use hf-internal-testing/tiny-random-MT5ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MT5ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MT5ForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MT5ForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MT5ForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0d5407d6cd5b0b0ca471b6b83850cb51920bf51e380e2d4b5b44b9f109f3db2
- Size of remote file:
- 32.2 MB
- SHA256:
- a972857548383d346c94922dd5341b8b2bc13924a26aa26eb80c9d1331207255
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