| --- |
| license: mit |
| tags: |
| - diffusion |
| - llm |
| - conversational |
| - difference-labs |
| datasets: |
| - smangrul/ultrachat-10k-chatml |
| base_model: |
| - darwinkernelpanic/DiffReaper-5L |
| --- |
| |
| # DiffReaper-6 |
|
|
| **DiffReaper-6** is a Large-scale Diffusion-based Large Language Model (Diffusion-LLM) developed by **DifferenceLabs**. |
|
|
| It represents a significant architectural leap over the previous 5L version, transitioning to a more robust denoiser and a deeper transformer-based backbone to achieve actual conversational coherence. |
|
|
| ## Model Details |
| - **Architecture**: Diffusion-Transformer (DiT) with Adaptive Layer Norm (adaLN-Single) modulation. |
| - **Backbone**: 24 Layers, 24 Attention Heads, 1536 Hidden Dimension. |
| - **Tokenizer**: BERT-base-uncased. |
| - **Training Objective**: MSE on Denoising Latents (Predicting original embeddings from noisy input). |
| - **Conditioning**: Prompt-concatenated latents with time-step embedding. |
|
|
| ## Training |
| The model is being trained on an RTX 5090 using the `ultrachat-10k` dataset, focusing on conversational flow and instruction following. |
|
|
| ## Goal |
| To prove that diffusion models can reach (and eventually exceed) the coherence of auto-regressive models while maintaining the creative "soul" and parallel generation benefits of diffusion. |
