Fix pipeline tag and link to paper

#1
by nielsr HF Staff - opened
Files changed (1) hide show
  1. README.md +21 -15
README.md CHANGED
@@ -1,28 +1,28 @@
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  ---
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- license: apache-2.0
 
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  language:
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  - en
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  - zh
 
 
 
 
 
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  tags:
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  - llama-factory
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  - easy-r1
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  - full
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  - generated_from_trainer
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- metrics:
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- - f1
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- base_model:
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- - Qwen/Qwen2.5-VL-7B-Instruct
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  model-index:
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- - name: GuardReasoner-VL-Eco-7B
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  results: []
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- pipeline_tag: text-classification
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- library_name: transformers
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  ---
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- # GuardReasoner-VL-Eco-7B
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- This model is a fine-tuned version of [Qwen/Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct) via R-SFT and online RL.
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- This model is based on the paper [GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning](https://arxiv.org/html/2505.11049v1).
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  <!-- The training data of R-SFT can be found in [GuardReasonerTrain](https://huggingface.co/datasets/yueliu1999/GuardReasonerTrain). -->
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@@ -37,7 +37,7 @@ from transformers import AutoProcessor
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  from qwen_vl_utils import process_vision_info
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  parser = argparse.ArgumentParser(description="GuardReasoner-VL Inference")
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- parser.add_argument("--model_path", type=str, default="yueliu1999/GuardReasoner-VL-Eco-7B", help="model path")
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  parser.add_argument("--benchmark_path", type=str, default="./data/benchmark/", help="benchmark path")
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  args = parser.parse_args()
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@@ -152,17 +152,23 @@ messages = [
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  case3_res = generate(messages)
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- print("case1:\n\n")
 
 
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  print("-"*30)
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  print(case1_res)
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  print("-"*30)
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- print("case2:\n\n")
 
 
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  print("-"*30)
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  print(case2_res)
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  print("-"*30)
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- print("case3:\n\n")
 
 
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  print("-"*30)
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  print(case3_res)
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  print("-"*30)
 
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  ---
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+ base_model:
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+ - Qwen/Qwen2.5-VL-3B-Instruct
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  language:
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  - en
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  - zh
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+ library_name: transformers
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+ license: apache-2.0
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+ metrics:
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+ - f1
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+ pipeline_tag: image-text-to-text
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  tags:
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  - llama-factory
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  - easy-r1
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  - full
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  - generated_from_trainer
 
 
 
 
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  model-index:
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+ - name: GuardReasoner-VL-3B
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  results: []
 
 
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  ---
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+ # GuardReasoner-VL-3B
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+ This model is a fine-tuned version of [Qwen/Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct) via R-SFT and online RL.
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+ This model is based on the paper [GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning](https://huggingface.co/papers/2505.11049).
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  <!-- The training data of R-SFT can be found in [GuardReasonerTrain](https://huggingface.co/datasets/yueliu1999/GuardReasonerTrain). -->
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  from qwen_vl_utils import process_vision_info
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  parser = argparse.ArgumentParser(description="GuardReasoner-VL Inference")
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+ parser.add_argument("--model_path", type=str, default="yueliu1999/GuardReasoner-VL-3B", help="model path")
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  parser.add_argument("--benchmark_path", type=str, default="./data/benchmark/", help="benchmark path")
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  args = parser.parse_args()
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  case3_res = generate(messages)
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+ print("case1:
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+
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+ ")
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  print("-"*30)
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  print(case1_res)
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  print("-"*30)
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+ print("case2:
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+
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+ ")
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  print("-"*30)
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  print(case2_res)
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  print("-"*30)
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+ print("case3:
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+
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+ ")
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  print("-"*30)
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  print(case3_res)
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  print("-"*30)