Instructions to use Mooshie/caformer_b36.dbv4-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Mooshie/caformer_b36.dbv4-full with timm:
import timm model = timm.create_model("hf_hub:Mooshie/caformer_b36.dbv4-full", pretrained=True) - Transformers
How to use Mooshie/caformer_b36.dbv4-full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Mooshie/caformer_b36.dbv4-full") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Mooshie/caformer_b36.dbv4-full", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| category,name,alpha,threshold,f1,precision,recall | |
| 0,general,1.0,0.39,0.6761805756074638,0.6723539158516435,0.680051043076706 | |
| 4,character,1.0,0.47000000000000003,0.9334669051873357,0.9529556146451217,0.9147593402894648 | |
| 9,rating,1.0,0.39,0.829527999163105,0.7915092283655986,0.8713833863871373 | |