Instructions to use slotwhisperer/symbols-mnv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slotwhisperer/symbols-mnv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="slotwhisperer/symbols-mnv3") 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("slotwhisperer/symbols-mnv3") model = AutoModelForImageClassification.from_pretrained("slotwhisperer/symbols-mnv3", device_map="auto") - timm
How to use slotwhisperer/symbols-mnv3 with timm:
import timm model = timm.create_model("hf_hub:slotwhisperer/symbols-mnv3", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 327c1ab03a8940b4c322840fd69cd8533e697b904bc65d5094ec91bcb0c74e1d
- Size of remote file:
- 5.39 kB
- SHA256:
- efd55dbbf50453e2ec1ca8b732c90b4894970d8d5fcbe7696239606b3dd08839
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