Instructions to use quasar529/rainbow-padding-llada with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use quasar529/rainbow-padding-llada with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("GSAI-ML/LLaDA-8B-Base") model = PeftModel.from_pretrained(base_model, "quasar529/rainbow-padding-llada") - Notebooks
- Google Colab
- Kaggle
metadata
base_model: GSAI-ML/LLaDA-8B-Base
library_name: peft
pipeline_tag: text-generation
tags:
- base_model:adapter:GSAI-ML/LLaDA-8B-Base
- lora
- transformers
- rainbow-padding
- instruct-tuning
Rainbow Padding LLaDA Instruct
We introduce Rainbow Padding, a cyclic multi-token padding scheme that eliminates early termination and restores length robustness in instruction-tuned diffusion LLMs.
This checkpoint is a LoRA adapter for LLaDA-8B-Base with Rainbow Padding applied.
Model Details
- Project Page: Rainbow Padding Official Website
- GitHub Repository: Rainbow Padding Implementation
- Paper: Rainbow Padding: Mitigating Early Termination in Instruction-Tuned Diffusion LLMs