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:
- 24a0fd37f67ce8e556a51c9acc1f8d267728d75a05c8d46e3e48f9cc65ff2d37
- Size of remote file:
- 32.1 MB
- SHA256:
- 3957620bbeb720f9c399f3b376a69ba5bdd0ff05f3d6a056186af2850264e164
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