Image Classification
Transformers
Safetensors
cls_vitdet
feature-extraction
multi-label
anime
custom_code
Instructions to use pixai-labs/pixai-tagger-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pixai-labs/pixai-tagger-v1.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pixai-labs/pixai-tagger-v1.0", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pixai-labs/pixai-tagger-v1.0", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download figures/release_comparison.csv from pixai-labs/pixai-tagger-v1.0: direct link, hf CLI and curl.
- Browser
- Download file 152 Bytes
-
https://huggingface.co/pixai-labs/pixai-tagger-v1.0/resolve/main/figures/release_comparison.csv
- Command line
-
hf download hf://pixai-labs/pixai-tagger-v1.0/figures/release_comparison.csv
-
curl -L -o release_comparison.csv https://huggingface.co/pixai-labs/pixai-tagger-v1.0/resolve/main/figures/release_comparison.csv
152 Bytes
| model,vocabulary,input_size,general_micro_f1,character_micro_f1 | |
| PixAI Tagger v0.9,13461,448,0.5980,0.8198 | |
| PixAI Tagger v1.0,30877,1008,0.6660,0.9242 | |