Instructions to use seayala/practica_2_model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seayala/practica_2_model2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="seayala/practica_2_model2")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("seayala/practica_2_model2") model = AutoModelForObjectDetection.from_pretrained("seayala/practica_2_model2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4640cd99ed43ba0d245976eb2b6201c17001fd92080192bf8f91c5fe05eec20c
- Size of remote file:
- 5.3 kB
- SHA256:
- abcc30bdddd821c5f0c645c500c2467ec9e94bf304cab0d8620eb3583be9838a
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