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:
- 9cbf75c27d565b798a30f62673b3f96b33800c95bd28ce9d6a9933212af2a89b
- Size of remote file:
- 258 kB
- SHA256:
- f041696337dc9d08b969ffcf9e9ab3838b1f71f03144e97bb989e71d116ddc7e
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