Image Classification
Transformers
TensorBoard
Safetensors
beit
Generated from Trainer
Eval Results (legacy)
Instructions to use ricardoSLabs/paper_model_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ricardoSLabs/paper_model_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ricardoSLabs/paper_model_2") 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_2") model = AutoModelForImageClassification.from_pretrained("ricardoSLabs/paper_model_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ricardoSLabs/paper_model_2: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/ricardoSLabs/paper_model_2/resolve/main/training_args.bin
- Command line
-
hf download hf://ricardoSLabs/paper_model_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ricardoSLabs/paper_model_2/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 7f20a22e6eb4869d449b66561a0f71d3e9d3aa11eb2236000e392fc98f68f63d
- Size of remote file:
- 5.11 kB
- SHA256:
- 26cd027ecb20135e7b164118a9d62e81ba6a319016d884cfb40767c50036acb0
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