Instructions to use hf-internal-testing/tiny-random-ConvBertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ConvBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-ConvBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ConvBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-ConvBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba3993a51e19085f40fa4a3799ab3a585bdd04bd1790bf76c1a762f1eb30a728
- Size of remote file:
- 5.48 MB
- SHA256:
- 9e5422539f74aade15bb50cc3f56f8fe50b8a5d21dfa24ff9bf1c7a26fbe77d6
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