Image Classification
Transformers
TensorBoard
Safetensors
resnet
Generated from Trainer
Eval Results (legacy)
Instructions to use ricardoSLabs/paper_model_DP_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ricardoSLabs/paper_model_DP_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ricardoSLabs/paper_model_DP_1") 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("ricardoSLabs/paper_model_DP_1") model = AutoModelForImageClassification.from_pretrained("ricardoSLabs/paper_model_DP_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ricardoSLabs/paper_model_DP_1: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/ricardoSLabs/paper_model_DP_1/resolve/main/training_args.bin
- Command line
-
hf download hf://ricardoSLabs/paper_model_DP_1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ricardoSLabs/paper_model_DP_1/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- e9a53d4633516c7bd4d5d903a2bd5c0b7c5bc13b8b96ba74d88964185c6ae84c
- Size of remote file:
- 5.11 kB
- SHA256:
- e50e181cbbff3dd0beda630a0ccfdd3fbf9d75f9fc05d5ea047e72c72cf92941
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