Instructions to use hf-internal-testing/tiny-random-DistilBertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DistilBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-DistilBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DistilBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-DistilBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e319f3883ff5abae540bf6e7af4c58ad202445696fbf0b3328eb7bb9592c49b
- Size of remote file:
- 355 kB
- SHA256:
- 5278d046cc9fcb6fdd00b0846b6a3764125e4d995ee6abc4a5d3e9c5dda39984
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