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:
- fc3e80142f45ba71fbd6b6a19967510414d226e88a62901dd02cb1cfdbecc7b9
- Size of remote file:
- 222 kB
- SHA256:
- 218cfcaf02203f8019c68adb4bb74e99fa8dfb8d7a6b8c9de5f279ea8a33f615
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