Instructions to use hf-internal-testing/tiny-random-MT5ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MT5ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-MT5ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MT5ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-MT5ForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4172b036d83b914d96d0e32fcd2c4934e61c049515f2314163c89795a5dff81
- Size of remote file:
- 32.1 MB
- SHA256:
- bb50b8dd568c7590379f84d014e5b7d352f4d687ee64af1697555e4a95dda0a8
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