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:
# pip install -U transformers accelerate # 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
Commit History
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Clarify DiBO prompt formatting
Verified signatureState that the inherited tokenizer chat template is not used by the DiBO training or evaluation path.2defed2 -
Set reinforcement-learning as the primary task
Verified signatureKeep DiBO diffusion-language-model and LLM tags while using the valid reinforcement-learning pipeline tag.8f47159 -
Add DiBO LLM discovery tag
Verified signatureExpose LLM and diffusion-language-model discovery tags while retaining the non-pipeline task classification.441295d -
Mark DiBO as a non-pipeline artifact
Verified signatureOverride the inferred feature-extraction task with pipeline_tag: other.f1375a1 -
Update public release metadata
Verified signaturePoint metadata to the public DiBO release commit and refresh model-card tags.8869ac1 -
Simplify model card artifact details
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Fix model-card installation reference
Verified signatureae9b10d -
Add validated TFBind10 dual-format release metadata
Verified signature592c3f7 -
Add validated Transformers safetensors export
Verified signature94f13ea
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Initial DiBO TFBind10 release
Verified signature159230c -
initial commit
Verified signature767ce27