Instructions to use hf-internal-testing/tiny-random-UMT5ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UMT5ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-UMT5ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-UMT5ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-UMT5ForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc519df18e594d61317edb4f4f0df2e463d184a47d106308aac022c9cab7c41f
- Size of remote file:
- 258 kB
- SHA256:
- 3052dd67c42d77a8e2675fe07a3adb123e0ca5bdebd912087944bdf92b7cdb7e
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