Instructions to use Mer0vin8ian/Gender-Classifier-Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mer0vin8ian/Gender-Classifier-Mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Mer0vin8ian/Gender-Classifier-Mini") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("Mer0vin8ian/Gender-Classifier-Mini") model = AutoModelForImageClassification.from_pretrained("Mer0vin8ian/Gender-Classifier-Mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,098 Bytes
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"best_global_step": 157,
"best_metric": 0.11236772686243057,
"best_model_checkpoint": "siglip2-finetune-full/checkpoint-157",
"epoch": 1.0,
"eval_steps": 500,
"global_step": 157,
"is_hyper_param_search": false,
"is_local_process_zero": true,
"is_world_process_zero": true,
"log_history": [
{
"epoch": 1.0,
"eval_accuracy": 0.9614,
"eval_loss": 0.11236772686243057,
"eval_model_preparation_time": 0.0024,
"eval_runtime": 61.0327,
"eval_samples_per_second": 81.923,
"eval_steps_per_second": 10.24,
"step": 157
}
],
"logging_steps": 500,
"max_steps": 314,
"num_input_tokens_seen": 0,
"num_train_epochs": 2,
"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": 4.1877747910656e+17,
"train_batch_size": 32,
"trial_name": null,
"trial_params": null
}
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