Add more tutorials for training and usage of GenerativeRL.

opendilab · Jun 28, 2024 · 6c246a5 · 6c246a5
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diff --git a/README.md b/README.md
@@ -44,7 +44,7 @@ English | [简体中文(Simplified Chinese)](https://github.com/opendilab/Genera
 | [Linear VP SDE](https://arxiv.org/abs/2011.13456)                                   | ✔                                                              | ✔                                                |
 | [Generalized VP SDE](https://arxiv.org/abs/2209.15571)                              | ✔                                                              | ✔                                                |
 | [Linear SDE](https://arxiv.org/abs/2206.00364)                                      | ✔                                                              | ✔                                                |
-| **Flow Model**                                                                      |                                                                 |                                                  |
+| **Flow Model**       [Colab](https://colab.research.google.com/drive/1vrxREVXKsSbnsv9G2CnKPVvrbFZleElI?usp=sharing)    |                              |                                                  |
 | [Independent Conditional Flow Matching](https://arxiv.org/abs/2302.00482)           |  🚫                                                            | ✔                                                |
 | [Optimal Transport Conditional Flow Matching](https://arxiv.org/abs/2302.00482)     |  🚫                                                            | ✔                                                |
 

diff --git a/README.zh.md b/README.zh.md
@@ -44,7 +44,7 @@
 | [Linear VP SDE](https://arxiv.org/abs/2011.13456)                                   | ✔                                                              | ✔                                                |
 | [Generalized VP SDE](https://arxiv.org/abs/2209.15571)                              | ✔                                                              | ✔                                                |
 | [Linear SDE](https://arxiv.org/abs/2206.00364)                                      | ✔                                                              | ✔                                                |
-| **流模型**                                                                           |                                                                |                                                   |
+| **流模型**      [Colab](https://colab.research.google.com/drive/1vrxREVXKsSbnsv9G2CnKPVvrbFZleElI?usp=sharing)    |                                   |                                                   |
 | [Independent Conditional Flow Matching](https://arxiv.org/abs/2302.00482)           | 🚫                                                             | ✔                                                 |
 | [Optimal Transport Conditional Flow Matching](https://arxiv.org/abs/2302.00482)     | 🚫                                                             | ✔                                                 |
 

diff --git a/grl_pipelines/tutorials/README.md b/grl_pipelines/tutorials/README.md
@@ -0,0 +1,23 @@
+# GenerativeRL Tutorials
+
+English | [简体中文(Simplified Chinese)](https://github.com/opendilab/GenerativeRL/tree/main/grl_pipelines/tutorials/README.zh.md)
+
+## Train a Generative Model
+
+### Diffusion Model
+
+We provide a simple colab notebook to demonstrate how to build a diffusion model using the `grl` library. You can access the notebook [here](https://colab.research.google.com/drive/18yHUAmcMh_7xq2U6TBCtcLKX2y4YvNyk#scrollTo=aqtDAvG6cQ1V).
+
+### Flow Model
+
+We provide a simple colab notebook to demonstrate how to build a flow model using the `grl` library. You can access the notebook [here](https://colab.research.google.com/drive/1vrxREVXKsSbnsv9G2CnKPVvrbFZleElI?usp=drive_link).
+
+## Evaluate a Generative Model
+
+### Sample Generation
+
+We provide a simple colab notebook to demonstrate how to generate samples from a trained generative model using the `grl` library. You can access the notebook [here](https://colab.research.google.com/drive/16jQhf1BDjtToxMZ4lDxB4IwGdRmr074j?usp=sharing).
+
+### Density Estimation
+
+We provide a simple colab notebook to demonstrate how to estimate the density of samples using a trained generative model using the `grl` library. You can access the notebook [here](https://colab.research.google.com/drive/1zHsW13n338YqX87AIWG26KLC4uKQL1ZP?usp=sharing).
diff --git a/grl_pipelines/tutorials/README.zh.md b/grl_pipelines/tutorials/README.zh.md
@@ -0,0 +1,23 @@
+# GenerativeRL 教程
+
+[英语 (English)](https://github.com/opendilab/GenerativeRL/tree/main/grl_pipelines/tutorials/README.md) | 简体中文
+
+## 训练生成模型
+
+### 扩散模型
+
+我们提供了一个简单的 colab 笔记本，演示如何使用 `grl` 库构建扩散模型。您可以在[这里](https://colab.research.google.com/drive/18yHUAmcMh_7xq2U6TBCtcLKX2y4YvNyk#scrollTo=aqtDAvG6cQ1V)访问笔记本。
+
+### 流模型
+
+我们提供了一个简单的 colab 笔记本，演示如何使用 `grl` 库构建流模型。您可以在[这里](https://colab.research.google.com/drive/1vrxREVXKsSbnsv9G2CnKPVvrbFZleElI?usp=drive_link)访问笔记本。
+
+## 评估生成模型
+
+### 采样生成
+
+我们提供了一个简单的 colab 笔记本，演示如何使用 `grl` 库从训练有素的生成模型生成样本。您可以在[这里](https://colab.research.google.com/drive/16jQhf1BDjtToxMZ4lDxB4IwGdRmr074j?usp=sharing)访问笔记本。
+
+### 概率密度估计
+
+我们提供了一个简单的 colab 笔记本，演示如何使用 `grl` 库从训练有素的生成模型估计样本的概率密度。您可以在[这里](https://colab.research.google.com/drive/1zHsW13n338YqX87AIWG26KLC4uKQL1ZP?usp=sharing)访问笔记本。