Instructions to use hf-tiny-model-private/tiny-random-ConvBertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-ConvBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-ConvBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 482ac28d2530991452e4767c8d21d9f4bf47b2adb6b23f376b97b5c7ba3d0432
- Size of remote file:
- 5.34 MB
- SHA256:
- f92b48722604e0f781aa63fcb99914b80d6a0ad4427fb6bc0c8670d5ac0ed9dd
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