LARK-Lab
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CodeScaler-1.7B

Text Classification

text-embeddings-inference

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shawnxzhu commited on 21 days ago

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@@ -7,7 +7,7 @@ tags:
 - CodeScaler
 license: mit
 datasets:
-- LARK-Lab/CodeScalerPair-52K
 language:
 - en
 base_model:
@@ -44,7 +44,7 @@ base_model:
 We propose **CodeScaler**, an execution-free reward model designed to scale both reinforcement learning training and test-time inference for code generation. **CodeScaler** is trained on carefully curated preference data derived from verified code problems and incorporates syntax-aware code extraction and validity-preserving reward shaping to ensure stable and robust optimization.
-This model is the official CodeScaler-1.7B trained from Skywork/Skywork-Reward-V2-Qwen3-1.7B on [LARK-Lab/CodeScalerPair-52K](https://huggingface.co/datasets/LARK-Lab/CodeScalerPair-52K).
 ## Performance on RM-Bench
 | Model                                | Code | Chat  | Math  | Safety | Easy  | Normal | Hard | Avg  |

 - CodeScaler
 license: mit
 datasets:
+- LARK-Lab/CodeScalerPair-51K
 language:
 - en
 base_model:
 We propose **CodeScaler**, an execution-free reward model designed to scale both reinforcement learning training and test-time inference for code generation. **CodeScaler** is trained on carefully curated preference data derived from verified code problems and incorporates syntax-aware code extraction and validity-preserving reward shaping to ensure stable and robust optimization.
+This model is the official CodeScaler-1.7B trained from Skywork/Skywork-Reward-V2-Qwen3-1.7B on [LARK-Lab/CodeScalerPair-51K](https://huggingface.co/datasets/LARK-Lab/CodeScalerPair-51K).
 ## Performance on RM-Bench
 | Model                                | Code | Chat  | Math  | Safety | Easy  | Normal | Hard | Avg  |