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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc443c9103d56b20b0bd5b0d807e96a8341b3ee2bb7c687c9bbae0597b75ff9d
- Size of remote file:
- 5.36 MB
- SHA256:
- 29b195514e89f942e34686305326cf1247404ce72f456bad6bffb978859b9e6a
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