Instructions to use hf-internal-testing/tiny-random-ResNetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ResNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-ResNetModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ResNetModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ResNetModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-ResNetModel: direct link, hf CLI and curl.
- Browser
- Download file 106 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-ResNetModel/resolve/9f3ff3f3340117f9a3e7d8e6fe80e7e985cfa53c/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-ResNetModel@9f3ff3f3340117f9a3e7d8e6fe80e7e985cfa53c/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-ResNetModel/resolve/9f3ff3f3340117f9a3e7d8e6fe80e7e985cfa53c/pytorch_model.bin
106 kB
- Xet hash:
- acf71d58f1c30ae0a29f8a95d29d064e355a285b52f5b7c8da062d5773cad8ad
- Size of remote file:
- 106 kB
- SHA256:
- 51e07d22afb52cc873b19bca5cd9b2276a413c234a609b62de494b4ccd03e73c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.