Instructions to use ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission") 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("ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission") model = AutoModelForImageClassification.from_pretrained("ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission/resolve/main/training_args.bin
- Command line
-
hf download hf://ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ZafarLocAI/convnext_checkpoints_mar20_classification_combat_mission/resolve/main/training_args.bin
5.27 kB
- Xet hash:
- a7761858bcbcb09737295459d8b0d55f1bec3b72d1e3412cd2567c0bb93ae179
- Size of remote file:
- 5.27 kB
- SHA256:
- c2c44cbb18778c0fd2842286325c8f5cef2b75badd70400286ec942dde01b281
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.