Instructions to use hf-internal-testing/tiny-random-T5ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-T5ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-T5ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-T5ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-T5ForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d428257887e6a3a15e9d18030007cd2cc55ba06f65a2290b80c77e150ecf860
- Size of remote file:
- 222 kB
- SHA256:
- 78dfe82247f5cac5984925ad4b85a4e33f0bc5e42f54b15894a2032eccaec56e
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