Instructions to use hf-internal-testing/tiny-random-ConvBertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ConvBertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-ConvBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ConvBertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ConvBertModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 526b5944bf8254d0e92087cdbe49a1afefee9ee3dd2fcd4883e9dba70c2fc163
- Size of remote file:
- 5.36 MB
- SHA256:
- c6add5f13a74889d98364eb608c629fcd8816647bd3c171e6d9f981ec77dc26b
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