Instructions to use TalentoTechIA/Hamilton with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TalentoTechIA/Hamilton with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TalentoTechIA/Hamilton") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("TalentoTechIA/Hamilton") model = AutoModelForImageClassification.from_pretrained("TalentoTechIA/Hamilton", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 390 Bytes
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"epoch": 4.0,
"eval_accuracy": 0.9849624060150376,
"eval_loss": 0.03612133860588074,
"eval_runtime": 2.2122,
"eval_samples_per_second": 60.122,
"eval_steps_per_second": 7.685,
"total_flos": 3.205097416476426e+17,
"train_loss": 0.12559190638936482,
"train_runtime": 410.5328,
"train_samples_per_second": 10.075,
"train_steps_per_second": 1.267
} |