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:
- 9972f83de67161c99014df318f1f40df67e0eceb1da5125336d00aee4280744f
- Size of remote file:
- 32.1 MB
- SHA256:
- 158cb5d29798e0f82239376bb451ed82f13b9e40939580f112e8b11fea85f1df
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