Instructions to use akkikiki/LLaDA-8B-Instruct-judge-fs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akkikiki/LLaDA-8B-Instruct-judge-fs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="akkikiki/LLaDA-8B-Instruct-judge-fs", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("akkikiki/LLaDA-8B-Instruct-judge-fs", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09e358c75137a0516aa7d23141d52e162568fd1e54b83d8704b0c1fb762bccb1
- Size of remote file:
- 5 GB
- SHA256:
- 311994af64990ce6797d872296ca6fa858fca7de494ee28e99629d673cd686e7
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