Instructions to use fxmarty/tiny-testing-remote-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fxmarty/tiny-testing-remote-code with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="fxmarty/tiny-testing-remote-code", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("fxmarty/tiny-testing-remote-code", trust_remote_code=True) model = AutoModelForImageClassification.from_pretrained("fxmarty/tiny-testing-remote-code", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download create_model.py from fxmarty/tiny-testing-remote-code: direct link, hf CLI and curl.
- Browser
- Download file 389 Bytes
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https://huggingface.co/fxmarty/tiny-testing-remote-code/resolve/77501cd311d982793f0df4dffacb9f7d0f4d3f33/create_model.py
- Command line
-
hf download hf://fxmarty/tiny-testing-remote-code@77501cd311d982793f0df4dffacb9f7d0f4d3f33/create_model.py
-
curl -L -o create_model.py https://huggingface.co/fxmarty/tiny-testing-remote-code/resolve/77501cd311d982793f0df4dffacb9f7d0f4d3f33/create_model.py
389 Bytes
| from transformers import AutoConfig | |
| from modeling.modeling_resnet import ResNetCustomForImageClassification | |
| cfg = AutoConfig.from_pretrained("microsoft/resnet-18") | |
| ResNetCustomForImageClassification.register_for_auto_class("AutoModelForImageClassification") | |
| model = ResNetCustomForImageClassification(cfg) | |
| model.save_pretrained("/home/fxmarty/hf_internship/tiny-testing-remote-code") | |