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:
- fb787b03ef8bb8c0894e043f6c0f969a7cfd528f35402ef4580e61e44d440b82
- Size of remote file:
- 32.2 MB
- SHA256:
- f4f9072931b3dac2103cac456ba9ae0380f23ddb81af390509e92cc0f41dac8e
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