tags:
- masked-diffusion
- diffusion
- qwen2
- code
language:
- en
pipeline_tag: text-generation
dlm-code0.6b-exp
Experimental masked-diffusion language model for code, from the thunder-fast project.
This is a discrete masked-diffusion (MDM) adaptation of a Qwen2-based pretrained code model (~0.5B). It is not an autoregressive next-token model: generation is a progressive un-masking loop under bidirectional attention, so a whole output window is filled in parallel over 24 diffusion steps.
Details
| Backbone | Qwen2 (model_type: qwen2), 24 layers, hidden 896, 14 attention / 2 KV heads, GQA |
| Vocabulary | 151,936 + <M> mask token (id 151665) |
| Diffusion | discrete [MASK], 24-step progressive un-masking, entropy-based position confidence (alg_temp 0.6, top_k 500) |
| Context | window-based (256 tokens) — not left-to-right; supports infilling |
| Weights | bf16 (model.safetensors) |
How to run
This checkpoint is intended to be driven by a diffusion decoder (bidirectional attention + the iterative un-masking loop), e.g. the thunder-fast runtime. Loading it as a plain causal Qwen2ForCausalLM will not reproduce diffusion generation.
# thunder-fast runtime (ggml engine) or the reference DiffusionLM
# e.g. runtime --model dlm-code0.6b-exp.gguf --prompt "..."
Status
Experimental / work-in-progress (.exp). It is a diffusion code-generation checkpoint published for the thunder-fast project; see the repo for training, the masking schedule, and evaluation details.