Instructions to use cvmil/deit-base-patch16-224_augmented-v2_tl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cvmil/deit-base-patch16-224_augmented-v2_tl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="cvmil/deit-base-patch16-224_augmented-v2_tl") 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("cvmil/deit-base-patch16-224_augmented-v2_tl") model = AutoModelForImageClassification.from_pretrained("cvmil/deit-base-patch16-224_augmented-v2_tl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download trainer_state.json from cvmil/deit-base-patch16-224_augmented-v2_tl: direct link, hf CLI and curl.
- Browser
- Download file 725 Bytes
-
https://huggingface.co/cvmil/deit-base-patch16-224_augmented-v2_tl/resolve/main/trainer_state.json
- Command line
-
hf download hf://cvmil/deit-base-patch16-224_augmented-v2_tl/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/cvmil/deit-base-patch16-224_augmented-v2_tl/resolve/main/trainer_state.json
725 Bytes
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0, | |
| "eval_steps": 500, | |
| "global_step": 0, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [], | |
| "logging_steps": 500, | |
| "max_steps": 1260, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 20, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": false, | |
| "should_training_stop": false | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 0, | |
| "train_batch_size": 128, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |