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:
- 127440fb5d94db5615c84b40c6e594e76a379296a5163803f17caf3546ef087b
- Size of remote file:
- 5 GB
- SHA256:
- ff727b629ad41665173cf98aa2195b60d4116d1be050f0cf0fd667f802a01fd1
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