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README.md
15
README.md
@ -138,6 +138,10 @@ pip install -e .
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### 📂 Data Preparation
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### 📂 Data Preparation
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You can choose one for the following method to prepare datasets.
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#### Offline Preparation
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You can download and extract the datasets with the following commands:
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You can download and extract the datasets with the following commands:
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```bash
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```bash
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@ -146,12 +150,19 @@ wget https://github.com/open-compass/opencompass/releases/download/0.2.2.rc1/Ope
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unzip OpenCompassData-core-20240207.zip
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unzip OpenCompassData-core-20240207.zip
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```
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```
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Also, use the [ModelScope](www.modelscope.cn) to load the datasets on demand.
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#### Automatic Download from OpenCompass
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We have supported download datasets automatic from the OpenCompass storage server. You can run the evaluation with extra `--dry-run` to download these datasets.
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Currently, the supported datasets are listed in [here](https://github.com/open-compass/opencompass/blob/main/opencompass/utils/datasets_info.py#L259). More datasets will be uploaded recently.
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#### (Optional) Automatic Download with ModelScope
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Also you can use the [ModelScope](www.modelscope.cn) to load the datasets on demand.
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Installation:
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Installation:
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```bash
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```bash
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pip install modelscope
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pip install modelscope[framework]
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export DATASET_SOURCE=ModelScope
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export DATASET_SOURCE=ModelScope
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```
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```
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@ -140,6 +140,8 @@ pip install -e .
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### 📂 数据准备
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### 📂 数据准备
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#### 提前离线下载
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OpenCompass支持使用本地数据集进行评测,数据集的下载和解压可以通过以下命令完成:
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OpenCompass支持使用本地数据集进行评测,数据集的下载和解压可以通过以下命令完成:
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```bash
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```bash
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@ -148,6 +150,13 @@ wget https://github.com/open-compass/opencompass/releases/download/0.2.2.rc1/Ope
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unzip OpenCompassData-core-20240207.zip
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unzip OpenCompassData-core-20240207.zip
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```
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```
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#### 从 OpenCompass 自动下载
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我们已经支持从OpenCompass存储服务器自动下载数据集。您可以通过额外的 `--dry-run` 参数来运行评估以下载这些数据集。
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目前支持的数据集列表在[这里](https://github.com/open-compass/opencompass/blob/main/opencompass/utils/datasets_info.py#L259)。更多数据集将会很快上传。
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#### (可选) 使用 ModelScope 自动下载
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另外,您还可以使用[ModelScope](www.modelscope.cn)来加载数据集:
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另外,您还可以使用[ModelScope](www.modelscope.cn)来加载数据集:
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环境准备:
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环境准备:
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@ -222,7 +222,7 @@ class VOLCRunner(BaseRunner):
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f.write(logs)
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f.write(logs)
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if task_status in [
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if task_status in [
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'Success', 'Failed', 'Cancelled', 'Exception',
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'Success', 'Failed', 'Cancelled', 'Exception',
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'Killing'
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'Killing', 'SuccessHolding', 'FailedHolding'
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]:
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]:
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break
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break
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time.sleep(poll_interval)
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time.sleep(poll_interval)
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