Image Classification
Transformers
Safetensors
English
siglip
Age
Detection
Siglip2
ViT
AutoImageProcessor
0-60+
Instructions to use prithivMLmods/Age-Classification-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Age-Classification-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Age-Classification-SigLIP2") 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("prithivMLmods/Age-Classification-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Age-Classification-SigLIP2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download checkpoint-595/trainer_state.json from prithivMLmods/Age-Classification-SigLIP2: direct link, hf CLI and curl.
- Browser
- Download file 1.29 kB
-
https://huggingface.co/prithivMLmods/Age-Classification-SigLIP2/resolve/48a079ee58df4cb0fb9e3dc17023d9d44b397cfa/checkpoint-595/trainer_state.json
- Command line
-
hf download hf://prithivMLmods/Age-Classification-SigLIP2@48a079ee58df4cb0fb9e3dc17023d9d44b397cfa/checkpoint-595/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/prithivMLmods/Age-Classification-SigLIP2/resolve/48a079ee58df4cb0fb9e3dc17023d9d44b397cfa/checkpoint-595/trainer_state.json
1.29 kB
| { | |
| "best_global_step": 595, | |
| "best_metric": 0.44112637639045715, | |
| "best_model_checkpoint": "siglip2-finetune-full/checkpoint-595", | |
| "epoch": 1.0, | |
| "eval_steps": 500, | |
| "global_step": 595, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.8403361344537815, | |
| "grad_norm": 37.12611770629883, | |
| "learning_rate": 4.034334763948498e-06, | |
| "loss": 0.757, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 1.0, | |
| "eval_accuracy": 0.8265671013883046, | |
| "eval_loss": 0.44112637639045715, | |
| "eval_model_preparation_time": 0.0026, | |
| "eval_runtime": 308.0267, | |
| "eval_samples_per_second": 61.735, | |
| "eval_steps_per_second": 7.717, | |
| "step": 595 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 2380, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 4, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": false | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 1.5927341304387502e+18, | |
| "train_batch_size": 32, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |