Instructions to use nclgbd/medsiglip-448-pneumonia-finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nclgbd/medsiglip-448-pneumonia-finetune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nclgbd/medsiglip-448-pneumonia-finetune") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("nclgbd/medsiglip-448-pneumonia-finetune") model = AutoModelForImageClassification.from_pretrained("nclgbd/medsiglip-448-pneumonia-finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-1500/optimizer.pt from nclgbd/medsiglip-448-pneumonia-finetune: direct link, hf CLI and curl.
- Browser
- Download file 3.43 GB
-
https://huggingface.co/nclgbd/medsiglip-448-pneumonia-finetune/resolve/main/checkpoint-1500/optimizer.pt
- Command line
-
hf download hf://nclgbd/medsiglip-448-pneumonia-finetune/checkpoint-1500/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/nclgbd/medsiglip-448-pneumonia-finetune/resolve/main/checkpoint-1500/optimizer.pt
3.43 GB
- Xet hash:
- ec643a3fe9fd5ca84079c1fd94d8feaa6c12b33b9b9ea32005366802a4b470e7
- Size of remote file:
- 3.43 GB
- SHA256:
- 6364535b45c08537d4b141ab0d0386f6f4e388dcf2649a8f44c86c55165e3ab3
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