Improve model card: add metadata and official links

#1
by nielsr HF Staff - opened
Files changed (1) hide show
  1. README.md +15 -2
README.md CHANGED
@@ -1,8 +1,21 @@
 
 
 
 
 
 
1
  # Qwen3-8B-A2D-untrained-dllm-convert
2
 
 
 
 
 
 
 
 
 
3
  Qwen3-8B converted to A2D architecture (bidirectional attention) using [dllm convert pipeline](https://github.com/ZHZisZZ/dllm/blob/b8d76ff74b2053d359cd88fedfbc6362db17e3d7/examples/a2d/README.md?plain=1#L49-L53).
4
 
5
- - **Base model**: [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B)
6
  - **Architecture**: A2D-Qwen3 (non-causal attention, same weights as original)
7
  - **Parameters**: 8.19B
8
  - **Vocab size**: 151936
@@ -10,4 +23,4 @@ Qwen3-8B converted to A2D architecture (bidirectional attention) using [dllm con
10
 
11
  This model has the original Qwen3-8B weights with bidirectional (non-causal) attention. No diffusion pretraining or SFT has been applied.
12
 
13
- **Mask token registration**: The mask token `<|MASK|>` (ID 151669) is registered in the tokenizer for use with diffusion-based language modeling. The original Qwen3 tokenizer includes `<|MASK|>` in `special_tokens_map.json` but does not register it in `tokenizer_config.json`, so `tokenizer.mask_token_id` returns `None`. We fixed this by adding `<|MASK|>` to the `added_tokens_decoder` section and the `mask_token` field in `tokenizer_config.json`, and adding the full `mask_token` entry in `special_tokens_map.json`. After this fix, `tokenizer.mask_token_id` correctly returns `151669`.
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: Qwen/Qwen3-8B
4
+ pipeline_tag: text-generation
5
+ ---
6
+
7
  # Qwen3-8B-A2D-untrained-dllm-convert
8
 
9
+ This repository contains the untrained initialization of Qwen3-8B converted to the A2D architecture (bidirectional attention), as introduced in the paper [Data-Efficient Autoregressive-to-Diffusion Language Models via On-Policy Distillation](https://huggingface.co/papers/2606.06712).
10
+
11
+ - **Project Page:** [https://opdlm.vercel.app/](https://opdlm.vercel.app/)
12
+ - **Code:** [https://github.com/divelab/OPDLM](https://github.com/divelab/OPDLM)
13
+ - **Base model:** [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B)
14
+
15
+ ## Model Details
16
+
17
  Qwen3-8B converted to A2D architecture (bidirectional attention) using [dllm convert pipeline](https://github.com/ZHZisZZ/dllm/blob/b8d76ff74b2053d359cd88fedfbc6362db17e3d7/examples/a2d/README.md?plain=1#L49-L53).
18
 
 
19
  - **Architecture**: A2D-Qwen3 (non-causal attention, same weights as original)
20
  - **Parameters**: 8.19B
21
  - **Vocab size**: 151936
 
23
 
24
  This model has the original Qwen3-8B weights with bidirectional (non-causal) attention. No diffusion pretraining or SFT has been applied.
25
 
26
+ **Mask token registration**: The mask token `<|MASK|>` (ID 151669) is registered in the tokenizer for use with diffusion-based language modeling. The original Qwen3 tokenizer includes `<|MASK|>` in `special_tokens_map.json` but does not register it in `tokenizer_config.json`, so `tokenizer.mask_token_id` returns `None`. We fixed this by adding `<|MASK|>` to the `added_tokens_decoder` section and the `mask_token` field in `tokenizer_config.json`, and adding the full `mask_token` entry in `special_tokens_map.json`. After this fix, `tokenizer.mask_token_id` correctly returns `151669`.