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ModelZoo
alphafold2_jax
Commits
a7d1b003
Commit
a7d1b003
authored
Jul 11, 2024
by
chenzk
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Revert "Merge branch 'master' into 'master'"
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README.md
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a7d1b003
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@@ -81,9 +81,6 @@ $DOWNLOAD_DIR/
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./scripts/download_all_data.sh 数据集下载目录
./scripts/download_all_data.sh 数据集下载目录
数据集快速下载中心:
[
SCNet AIDatasets
](
http://113.200.138.88:18080/aidatasets
)
,项目中数据集可从快速下载通道下载:
[
alphafold
](
http://113.200.138.88:18080/aidatasets/project-dependency/alphafold
)
。
## 推理
## 推理
分别提供了基于Jax的单体和多体的推理脚本.
分别提供了基于Jax的单体和多体的推理脚本.
```
bash
```
bash
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<div
style=
"display: flex; justify-content: center; align-items: center;"
>
<div
style=
"display: flex; justify-content: center; align-items: center;"
>
<img
src=
"./docs/result_pdb.png"
alt=
"Image"
>
<img
src=
"./docs/result_pdb.png"
alt=
"Image"
>
<div
style=
"position: absolute; top: 50%; left: 50%; transform: translate(-50%, -50%); background: rgba(0, 0, 0, 0.5); color: #fff; padding: 10px;"
>
<div
style=
"position: absolute; top: 50%; left: 50%; transform: translate(-50%, -50%); background: rgba(0, 0, 0, 0.5); color: #fff; padding: 10px;"
>
红色为真实结构,蓝色为预测结构
。
红色为真实结构,蓝色为预测结构
</div>
</div>
</div>
</div>
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## 应用场景
## 应用场景
### 算法类别
### 算法类别
蛋白质预测
NLP
### 热点应用行业
### 热点应用行业
医疗,科研,教育
医疗,科研,教育
## 预训练权重
预训练权重快速下载中心:
[
SCNet AIModels
](
http://113.200.138.88:18080/aimodels
)
,项目中的预训练权重可从快速下载通道下载:
[
alphafold
](
http://113.200.138.88:18080/aimodels/findsource-dependency/alphafold-params
)
。
## 源码仓库及问题反馈
## 源码仓库及问题反馈
*
[
https://developer.hpccube.com/codes/modelzoo/alphafold2_jax
](
https://developer.hpccube.com/codes/modelzoo/alphafold2_jax
)
*
[
https://developer.hpccube.com/codes/modelzoo/alphafold2_jax
](
https://developer.hpccube.com/codes/modelzoo/alphafold2_jax
)
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model.properties
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@@ -5,6 +5,6 @@ modelName=alphafold2_jax
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# 模型描述
# 模型描述
modelDescription
=
AlphaFold2是一个用于预测蛋白质三维结构的深度学习模型
modelDescription
=
AlphaFold2是一个用于预测蛋白质三维结构的深度学习模型
# 应用场景(多个标签以英文逗号分割)
# 应用场景(多个标签以英文逗号分割)
appScenario
=
推理,医疗,科研
,教育
appScenario
=
推理,
NLP,蛋白质结构预测,
医疗,科研
# 框架类型(多个标签以英文逗号分割)
# 框架类型(多个标签以英文逗号分割)
frameType
=
jax,tensorflow
frameType
=
jax,tensorflow
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