Zero-Shot Classification
Transformers
qwen3_5
feature-extraction
decision-model
system-one
classification
ternary
2-bit
lora
custom_code
Instructions to use BoldingBuilds/Wildcat-Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BoldingBuilds/Wildcat-Mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="BoldingBuilds/Wildcat-Mini", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("BoldingBuilds/Wildcat-Mini", trust_remote_code=True) model = AutoModel.from_pretrained("BoldingBuilds/Wildcat-Mini", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download NOTICE from BoldingBuilds/Wildcat-Mini: direct link, hf CLI and curl.
- Browser
- Download file 100 Bytes
-
https://huggingface.co/BoldingBuilds/Wildcat-Mini/resolve/main/NOTICE
- Command line
-
hf download hf://BoldingBuilds/Wildcat-Mini/NOTICE
-
curl -L -o NOTICE https://huggingface.co/BoldingBuilds/Wildcat-Mini/resolve/main/NOTICE
100 Bytes
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