Instructions to use TeraflopAI/logo-detection-m4-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use TeraflopAI/logo-detection-m4-224 with timm:
import timm model = timm.create_model("hf-hub:TeraflopAI/logo-detection-m4-224", pretrained=True) - Transformers
How to use TeraflopAI/logo-detection-m4-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TeraflopAI/logo-detection-m4-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("TeraflopAI/logo-detection-m4-224") model = AutoModel.from_pretrained("TeraflopAI/logo-detection-m4-224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="TeraflopAI/logo-detection-m4-224")
pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate
# Load model directly
from transformers import AutoImageProcessor, AutoModel
processor = AutoImageProcessor.from_pretrained("TeraflopAI/logo-detection-m4-224")
model = AutoModel.from_pretrained("TeraflopAI/logo-detection-m4-224", device_map="auto")Quick Links
- Downloads last month
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