Instructions to use hf-tiny-model-private/tiny-random-ConvBertModel 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-ConvBertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-ConvBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7e233bf3cc302c8f4cd266e69da93a0adf361ae39046857bb490d2411838928
- Size of remote file:
- 5.33 MB
- SHA256:
- 4436e2d0af46fd13d2a6e5e46bdfdfc59963b0537a1e9a303e901daf2be91414
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