Improve model card: add metadata and official links
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by nielsr HF Staff - opened
README.md
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# Qwen3-8B-A2D-untrained-dllm-convert
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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).
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- **Base model**: [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B)
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- **Architecture**: A2D-Qwen3 (non-causal attention, same weights as original)
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- **Parameters**: 8.19B
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- **Vocab size**: 151936
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This model has the original Qwen3-8B weights with bidirectional (non-causal) attention. No diffusion pretraining or SFT has been applied.
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**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`.
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---
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license: apache-2.0
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base_model: Qwen/Qwen3-8B
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pipeline_tag: text-generation
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---
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# Qwen3-8B-A2D-untrained-dllm-convert
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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).
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- **Project Page:** [https://opdlm.vercel.app/](https://opdlm.vercel.app/)
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- **Code:** [https://github.com/divelab/OPDLM](https://github.com/divelab/OPDLM)
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- **Base model:** [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B)
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## Model Details
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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).
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- **Architecture**: A2D-Qwen3 (non-causal attention, same weights as original)
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- **Parameters**: 8.19B
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- **Vocab size**: 151936
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This model has the original Qwen3-8B weights with bidirectional (non-causal) attention. No diffusion pretraining or SFT has been applied.
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**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`.
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