Instructions to use hf-internal-testing/tiny-random-PerceiverModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PerceiverModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-PerceiverModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PerceiverModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-PerceiverModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-PerceiverModel: direct link, hf CLI and curl.
- Browser
- Download file 193 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-PerceiverModel/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-PerceiverModel@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-PerceiverModel/resolve/refs%2Fpr%2F1/model.safetensors
193 kB
- Xet hash:
- 52ef5d78b1c13ea138e4a1966ec707cb88a60ef32b9aa2dcebbd7195631d9619
- Size of remote file:
- 193 kB
- SHA256:
- 9a36c57440da654f704681fb20fdbe7dfb7570ac9bc4a0c9bd9027e1091aab62
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