Instructions to use tarsur909/LLaDA-8B-Base-JSON-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tarsur909/LLaDA-8B-Base-JSON-SFT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="tarsur909/LLaDA-8B-Base-JSON-SFT", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tarsur909/LLaDA-8B-Base-JSON-SFT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa7907313e4c9117e5c8b696b1bd4115a0b2636d11fe497cbcd769534e0da828
- Size of remote file:
- 4.97 GB
- SHA256:
- b9e5f52506fc49233048e0f54ee0ed19b9a9707ccf6400701ad816ef96dcaaed
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