Instructions to use hf-internal-testing/tiny-random-onnx-convbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-onnx-convbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-onnx-convbert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-onnx-convbert") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-onnx-convbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6c1fdd791d76a6ba45fd423de3528f71b885c6769b3873faa04a515c0241060
- Size of remote file:
- 95.6 MB
- SHA256:
- 9f9a1510929fffd3c4a502f068ce14ccdb7f189598b33eeba266135b701e68f4
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