Instructions to use adventureshin/Bingsu-concept with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adventureshin/Bingsu-concept with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="adventureshin/Bingsu-concept")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("adventureshin/Bingsu-concept") model = AutoModel.from_pretrained("adventureshin/Bingsu-concept", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from adventureshin/Bingsu-concept: direct link, hf CLI and curl.
- Browser
- Download file 1.2 MB
-
https://huggingface.co/adventureshin/Bingsu-concept/resolve/main/tokenizer.json
- Command line
-
hf download hf://adventureshin/Bingsu-concept/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/adventureshin/Bingsu-concept/resolve/main/tokenizer.json
1.2 MB
File too large to display, you can check the raw version instead.