Feature Extraction
Transformers
Safetensors
llada
diffusion-language-model
dllm
LLaDA
WINO
WINO-plus
custom_code
Instructions to use QinFFF/WINO-plus-LLaDA-8B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QinFFF/WINO-plus-LLaDA-8B-Instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="QinFFF/WINO-plus-LLaDA-8B-Instruct", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("QinFFF/WINO-plus-LLaDA-8B-Instruct", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from QinFFF/WINO-plus-LLaDA-8B-Instruct: direct link, hf CLI and curl.
- Browser
- Download file 9.75 MB
-
https://huggingface.co/QinFFF/WINO-plus-LLaDA-8B-Instruct/resolve/main/tokenizer.json
- Command line
-
hf download hf://QinFFF/WINO-plus-LLaDA-8B-Instruct/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/QinFFF/WINO-plus-LLaDA-8B-Instruct/resolve/main/tokenizer.json
9.75 MB
File too large to display, you can check the raw version instead.