Reinforcement Learning
Transformers
Safetensors
llada
feature-extraction
llm
diffusion-language-model
black-box-optimization
offline-black-box-optimization
design-bench
dibo
custom_code
Instructions to use zpointsun/DiBO-TFBind8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zpointsun/DiBO-TFBind8 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zpointsun/DiBO-TFBind8", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| # Upstream LLaDA code notice | |
| `configuration_llada.py` and `modeling_llada.py` are copied from [`GSAI-ML/LLaDA-8B-Instruct`](https://huggingface.co/GSAI-ML/LLaDA-8B-Instruct) revision `08b83a6feb34df1a6011b80c3c00c7563e963b07`. The base model card declares the MIT license. The copied files remain subject to the upstream terms. `modeling_dibo_llada.py` is DiBO release code. | |