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-TFBind10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zpointsun/DiBO-TFBind10 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zpointsun/DiBO-TFBind10", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5bab4741eaddf91aa04e310e5144eeddac326e7d724c3e97e0cb0d05a3f0147
- Size of remote file:
- 16 GB
- SHA256:
- c59f6fa207da0bedaa32358d14a5993f82114cd9291cfab43dba07a40762bb2f
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