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qwen2_5_vl
nielsr HF Staff commited on
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1 Parent(s): c2a60d9

Add pipeline tag, library name, and paper link

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This PR improves the model card by:
- Adding `pipeline_tag: image-text-to-text` to better categorize the model on the Hub and improve discoverability.
- Adding `library_name: transformers` to enable the automated "how to use" widget, as the model is compatible with the 🤗 Transformers library as evidenced by the `Usage` section.
- Adding a direct link to the associated paper: [MedVLSynther: Synthesizing High-Quality Visual Question Answering from Medical Documents with Generator-Verifier LMMs](https://huggingface.co/papers/2510.25867) to the top of the content for easier access.

Files changed (1) hide show
  1. README.md +10 -5
README.md CHANGED
@@ -1,17 +1,20 @@
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  ---
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- license: apache-2.0
 
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  datasets:
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  - MedVLSynther/MedSynVQA-5K-SFT
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  language:
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  - en
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- base_model:
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- - Qwen/Qwen2.5-VL-3B-Instruct
 
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  ---
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  # MedVLThinker-3B-SFT_5K
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  Code: https://github.com/UCSC-VLAA/MedVLSynther
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  Project Page: https://ucsc-vlaa.github.io/MedVLSynther/
 
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  ## Model Description
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@@ -47,7 +50,8 @@ processor = AutoProcessor.from_pretrained(model_name)
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  messages_1 = [
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  {
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  "role": "system",
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- "content": "You will solve a problem/request. You should provide your thoughts within <think> </think> tags before providing the answer.\nWrite your final answer within <answer> </answer> tags.",
 
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  },
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  {
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  "role": "user",
@@ -64,7 +68,8 @@ messages_1 = [
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  messages_2 = [
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  {
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  "role": "system",
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- "content": "You will solve a problem/request. You should provide your thoughts within <think> </think> tags before providing the answer.\nWrite your final answer within <answer> </answer> tags.",
 
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  },
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  {
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  "role": "user",
 
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  ---
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+ base_model:
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+ - Qwen/Qwen2.5-VL-3B-Instruct
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  datasets:
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  - MedVLSynther/MedSynVQA-5K-SFT
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  language:
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  - en
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+ license: apache-2.0
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+ pipeline_tag: image-text-to-text
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+ library_name: transformers
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  ---
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  # MedVLThinker-3B-SFT_5K
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  Code: https://github.com/UCSC-VLAA/MedVLSynther
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  Project Page: https://ucsc-vlaa.github.io/MedVLSynther/
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+ Paper: [MedVLSynther: Synthesizing High-Quality Visual Question Answering from Medical Documents with Generator-Verifier LMMs](https://huggingface.co/papers/2510.25867)
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  ## Model Description
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  messages_1 = [
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  {
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  "role": "system",
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+ "content": "You will solve a problem/request. You should provide your thoughts within <think> </think> tags before providing the answer.
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+ Write your final answer within <answer> </answer> tags.",
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  },
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  {
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  "role": "user",
 
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  messages_2 = [
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  {
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  "role": "system",
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+ "content": "You will solve a problem/request. You should provide your thoughts within <think> </think> tags before providing the answer.
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+ Write your final answer within <answer> </answer> tags.",
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  },
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  {
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  "role": "user",