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:
- 1c488938a9eaa5a4c33f19c3369c6c0e2b649252af5995894b8e2b7c76ed3057
- Size of remote file:
- 258 kB
- SHA256:
- 7fe1d506a12755c360e5148f12af1fa619946a40541025cc83d29c1bac5b9ff8
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