Update README.md
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README.md
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@@ -62,13 +62,14 @@ To simplify the comparison, we chosed the Pass@1 metric for the Python language,
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| Model | HumanEval python pass@1 |
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| --- |----------------------------------------------------------------------------- |
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| CodeLlama-7b-hf | 30.5%|
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| opencsg-CodeLlama-7b-v0.1 | **43.9%** |
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| CodeLlama-13b-hf | 36.0%|
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| opencsg-CodeLlama-13b-v0.1 | **51.2%** |
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| CodeLlama-34b-hf | 48.2%|
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| opencsg-CodeLlama-34b-v0.1
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| opencsg-CodeLlama-34b-v0.2
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**TODO**
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- We will provide more benchmark scores on fine-tuned models in the future.
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@@ -176,12 +177,14 @@ HumanEval 是评估模型在代码生成方面性能的最常见的基准,尤
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| 模型 | HumanEval python pass@1 |
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| --- |----------------------------------------------------------------------------- |
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| CodeLlama-7b-hf | 30.5%|
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| opencsg-CodeLlama-7b-v0.1 | **43.9%** |
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| CodeLlama-13b-hf | 36.0%|
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| opencsg-CodeLlama-13b-v0.1 | **51.2%** |
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| CodeLlama-34b-hf | 48.2%|
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| opencsg-CodeLlama-34b-v0.1
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| opencsg-CodeLlama-34b-v0.
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**TODO**
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- 未来我们将提供更多微调模型的在各基准上的分数。
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| Model | HumanEval python pass@1 |
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| --- |----------------------------------------------------------------------------- |
|
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| CodeLlama-7b-hf | 30.5%|
|
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+
| **opencsg-CodeLlama-7b-v0.1** | **43.9%** |
|
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| CodeLlama-13b-hf | 36.0%|
|
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+
| **opencsg-CodeLlama-13b-v0.1** | **51.2%** |
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| CodeLlama-34b-hf | 48.2%|
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+
| **opencsg-CodeLlama-34b-v0.1**| **56.1%** |
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| **opencsg-CodeLlama-34b-v0.2**| **64.0%** |
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| CodeLlama-70b-hf| 53.0% |
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| CodeLlama-70b-Instruct-hf| **67.8%** |
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**TODO**
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- We will provide more benchmark scores on fine-tuned models in the future.
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| 模型 | HumanEval python pass@1 |
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| --- |----------------------------------------------------------------------------- |
|
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| CodeLlama-7b-hf | 30.5%|
|
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+
| **opencsg-CodeLlama-7b-v0.1** | **43.9%** |
|
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| CodeLlama-13b-hf | 36.0%|
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+
| **opencsg-CodeLlama-13b-v0.1** | **51.2%** |
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| CodeLlama-34b-hf | 48.2%|
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+
| **opencsg-CodeLlama-34b-v0.1**| **56.1%** |
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| **opencsg-CodeLlama-34b-v0.2**| **64.0%** |
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| CodeLlama-70b-hf| 53.0% |
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+
| CodeLlama-70b-Instruct-hf| **67.8%** |
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**TODO**
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- 未来我们将提供更多微调模型的在各基准上的分数。
|