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2 changes: 1 addition & 1 deletion LICENSE
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Expand Up @@ -198,4 +198,4 @@
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
limitations under the License.
4 changes: 2 additions & 2 deletions README.md
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# QuickStart Demo
# QuickStart Demo

查看服务实例部署在线文档,请访问 [服务实例部署文档](https://aliyun-computenest.github.io/quickstart-alphafold2)

Expand All @@ -15,4 +15,4 @@ $ mkdocs serve # in root folder

3)本地新建分支后,提交 `Pull request` 到 `main`分支。

4)合并至 `main` 分支后,查看 pages 部署结果。
4)合并至 `main` 分支后,查看 pages 部署结果。
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1 change: 1 addition & 0 deletions docs/gs.log
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test00111
3 changes: 2 additions & 1 deletion docs/index.md
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Expand Up @@ -17,7 +17,7 @@ MLflow不仅支持主流的机器学习库(如TensorFlow、PyTorch和scikit-le
## 前提条件

部署AlphaFold2社区版服务实例,需要对部分阿里云资源进行访问和创建操作。因此您的账号需要包含如下资源的权限。
**说明**:当您的账号是RAM账号时,才需要添加此权限
**说明**:当您的账号是RAM账号时,才需要添加此权限

| 权限策略名称 | 备注 |
|---------------------------------|------------------------|
Expand Down Expand Up @@ -73,6 +73,7 @@ MLflow社区版在计算巢部署的费用主要涉及:
5. 部署完成后,可以通过查看MLflow服务访问URL,访问ui页面或者在模型中集成服务地址
## 使用MLflow管理模型和实验
例如,如果您在 IP 地址**192.168.0.1**和端口**5000**的计算机上运行上述命令,则可以通过以下方式向其添加跟踪数据:

```python
mlflow.set_tracking_uri("http://192.168.0.1:5000")
mlflow.autolog() # Or other tracking functions
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