Instructions to use hf-internal-testing/tiny-random-VisualBertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-VisualBertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-VisualBertModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-VisualBertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-VisualBertModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-VisualBertModel: direct link, hf CLI and curl.
- Browser
- Download file 436 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-VisualBertModel/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-VisualBertModel@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-VisualBertModel/resolve/refs%2Fpr%2F1/model.safetensors
436 kB
- Xet hash:
- 91a09a604b53da1f6ec2611f4c786dfde0fbca8b667769158207f80adf9b0168
- Size of remote file:
- 436 kB
- SHA256:
- 27643c6c3db3742b7b08b61d007556e736c5cf8943f6d0b7beef63b218696c97
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