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:
- 60f0b4bc4e2287e7049884bd475c9ba8df7f0e4c883dcf9eb6898366a28410c6
- Size of remote file:
- 32.2 MB
- SHA256:
- cae20b81e4a003f2b993a2796f39aacfbbd1b6fd26a7b88bca1e02c8c41d1c8d
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