Instructions to use TalentoTechIA/Melissa_24_05_25 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TalentoTechIA/Melissa_24_05_25 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TalentoTechIA/Melissa_24_05_25") 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/Melissa_24_05_25") model = AutoModelForImageClassification.from_pretrained("TalentoTechIA/Melissa_24_05_25", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc432420ba811dd80e8c81f397d239ae3d24d3fc11734eccc9aba20a6db0f17c
- Size of remote file:
- 5.37 kB
- SHA256:
- bbb810df079d610a24fe982af666e041aa71acbd98fa76929f6ca967e8c2cae7
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