docs: add colab link

SwanHubX · Dec 4, 2024 · 6e6057d · 6e6057d
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diff --git a/en/examples/hello_world.md b/en/examples/hello_world.md
@@ -1,5 +1,7 @@
 # Hello World
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1RWsrY_1bS8ECzaHvYtLb_1eBkkdzekR3?usp=sharing)
+
 This is an introductory case, a minimal simulation of deep learning training.
 
 ## Environment Setup

diff --git a/en/guide_cloud/integration/integration-huggingface-transformers.md b/en/guide_cloud/integration/integration-huggingface-transformers.md
@@ -1,5 +1,7 @@
 # 🤗HuggingFace Transformers
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1iYwrAM4ToCWt5p5hlrrkHlQqBIav_r2E?usp=sharing)
+
 Hugging Face's [Transformers](https://github.com/huggingface/transformers) is a very popular open-source library that provides a large number of pre-trained models, primarily for natural language processing (NLP) tasks. The goal of this library is to make the latest models easy to use and support multiple frameworks such as TensorFlow and PyTorch.
 
 ![hf-transformers-image](/assets/ig-huggingface-transformers.png)

diff --git a/en/guide_cloud/integration/integration-pytorch-lightning.md b/en/guide_cloud/integration/integration-pytorch-lightning.md
@@ -1,5 +1,7 @@
 # PyTorch Lightning
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1g1s86qobSvIuaFVxzDgzyZ-B4VzdTCym?usp=sharing)
+
 [PyTorch Lightning](https://github.com/Lightning-AI/pytorch-lightning) is an open-source machine learning library built on top of PyTorch, designed to help researchers and developers more conveniently develop deep learning models. The design philosophy of Lightning is to separate the tedious code in model training (such as device management, distributed training, etc.) from the research code (model architecture, data processing, etc.), so that researchers can focus on the research itself rather than the underlying engineering details.
 
 ![pytorch-lightning-image](/assets/ig-pytorch-lightning.png)

diff --git a/en/guide_cloud/integration/integration-pytorch.md b/en/guide_cloud/integration/integration-pytorch.md
@@ -1,5 +1,7 @@
 # PyTorch
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1RWsrY_1bS8ECzaHvYtLb_1eBkkdzekR3?usp=sharing)
+
 Among academic researchers, [PyTorch](https://pytorch.org/) is the most popular Python deep learning framework.
 
 ![PyTorch](/assets/ig-pytorch.png)

diff --git a/en/guide_cloud/integration/integration-sb3.md b/en/guide_cloud/integration/integration-sb3.md
@@ -1,5 +1,7 @@
 # Stable-Baseline3
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1JfU4oCKCS7FQE_AXqZ3k9Bt1vmK-6pMO?usp=sharing)
+
 Stable Baselines3 (SB3) is an open-source reinforcement learning library built on the PyTorch framework. It is the successor to the Stable Baselines project, aiming to provide a set of reliable and well-tested RL algorithm implementations for research and application. Stable Baselines3 is primarily used in fields such as robotics control, game AI, autonomous driving, and financial trading.
 
 ![sb3](/assets/ig-sb3.png)

diff --git a/en/guide_cloud/integration/integration-swift.md b/en/guide_cloud/integration/integration-swift.md
@@ -1,5 +1,7 @@
 # Modelscope Swift
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1eAxKyTiLXLcQw7EOQngjV2csf5UdNQY4?usp=sharing)
+
 [Modelscope](https://modelscope.cn/) [Swift](https://github.com/modelscope/swift) is a framework that integrates model training, fine-tuning, inference, and deployment.
 
 SWIFT supports the training, inference, evaluation, and deployment of over 250 LLMs and 35+ MLLMs (multimodal large models). Developers can directly apply Swift to their research and production environments, achieving a complete pipeline from model training and evaluation to application. In addition to supporting lightweight training solutions provided by PEFT, Swift also offers a comprehensive Adapters library to support the latest training techniques such as NEFTune, LoRA+, LLaMA-PRO, etc. This adapter library can be used directly in custom workflows without relying on training scripts.

diff --git a/en/guide_cloud/integration/integration-ultralytics.md b/en/guide_cloud/integration/integration-ultralytics.md
@@ -1,5 +1,7 @@
 # Ultralytics
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1RAT2vSrvET4wEDd9syeDrgz0KBUDQAR1?usp=sharing)
+
 [Ultralytics](https://github.com/ultralytics/ultralytics) YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds on the success of previous YOLO versions and introduces new features and improvements to further enhance performance and flexibility. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a variety of object detection and tracking, instance segmentation, image classification, and pose estimation tasks.
 
 ![ultralytics](/assets/ig-ultralytics.png)

diff --git a/zh/examples/hello_world.md b/zh/examples/hello_world.md
@@ -1,5 +1,7 @@
 # Hello World
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1RWsrY_1bS8ECzaHvYtLb_1eBkkdzekR3?usp=sharing)
+
 这是一个入门案例，是一个最简的深度学习训练模拟。
 
 ## 环境准备

diff --git a/zh/guide_cloud/integration/integration-huggingface-transformers.md b/zh/guide_cloud/integration/integration-huggingface-transformers.md
@@ -1,5 +1,7 @@
 # 🤗HuggingFace Transformers
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1iYwrAM4ToCWt5p5hlrrkHlQqBIav_r2E?usp=sharing)
+
 Hugging Face 的 [Transformers](https://github.com/huggingface/transformers) 是一个非常流行的开源库，它提供了大量预训练的模型，主要用于自然语言处理（NLP）任务。这个库的目标是使最新的模型能够易于使用，并支持多种框架，如 TensorFlow 和 PyTorch。
 
 ![hf-transformers-image](/assets/ig-huggingface-transformers.png)

diff --git a/zh/guide_cloud/integration/integration-pytorch-lightning.md b/zh/guide_cloud/integration/integration-pytorch-lightning.md
@@ -1,5 +1,7 @@
 # PyTorch Lightning
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1g1s86qobSvIuaFVxzDgzyZ-B4VzdTCym?usp=sharing)
+
 [PyTorch Lightning](https://github.com/Lightning-AI/pytorch-lightning)是一个开源的机器学习库，它建立在 PyTorch 之上，旨在帮助研究人员和开发者更加方便地进行深度学习模型的研发。Lightning 的设计理念是将模型训练中的繁琐代码（如设备管理、分布式训练等）与研究代码（模型架构、数据处理等）分离，从而使研究人员可以专注于研究本身，而不是底层的工程细节。
 
 ![pytorch-lightning-image](/assets/ig-pytorch-lightning.png)

diff --git a/zh/guide_cloud/integration/integration-pytorch.md b/zh/guide_cloud/integration/integration-pytorch.md
@@ -1,5 +1,7 @@
 # PyTorch
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1RWsrY_1bS8ECzaHvYtLb_1eBkkdzekR3?usp=sharing)
+
 在学术研究者当中，[PyTorch](https://pytorch.org/) 是最流行的 Python 深度学习框架。  
 
 ![PyTorch](/assets/ig-pytorch.png)

diff --git a/zh/guide_cloud/integration/integration-sb3.md b/zh/guide_cloud/integration/integration-sb3.md
@@ -1,5 +1,8 @@
 # Stable-Baseline3
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1JfU4oCKCS7FQE_AXqZ3k9Bt1vmK-6pMO?usp=sharing)
+
+
 Stable Baselines3 (SB3) 是一个强化学习的开源库，基于 PyTorch 框架构建。它是 Stable Baselines 项目的继任者，旨在提供一组可靠且经过良好测试的RL算法实现，便于研究和应用。StableBaseline3主要被应用于机器人控制、游戏AI、自动驾驶、金融交易等领域。
 
 ![sb3](/assets/ig-sb3.png)

diff --git a/zh/guide_cloud/integration/integration-swift.md b/zh/guide_cloud/integration/integration-swift.md
@@ -1,5 +1,7 @@
 # Modelscope Swift
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1eAxKyTiLXLcQw7EOQngjV2csf5UdNQY4?usp=sharing)
+
 [Modelscope魔搭社区](https://modelscope.cn/) 的 [Swift](https://github.com/modelscope/swift) 是一个集模型训练、微调、推理、部署于一体的框架。
 
 SWIFT支持250+ LLM和35+ MLLM（多模态大模型）的训练、推理、评测和部署。开发者可以直接将Swift应用到自己的Research和生产环境中，实现模型训练评测到应用的完整链路。Swift除支持了PEFT提供的轻量训练方案外，也提供了一个完整的Adapters库以支持最新的训练技术，如NEFTune、LoRA+、LLaMA-PRO等，这个适配器库可以脱离训练脚本直接使用在自己的自定流程中。

diff --git a/zh/guide_cloud/integration/integration-ultralytics.md b/zh/guide_cloud/integration/integration-ultralytics.md
@@ -1,5 +1,7 @@
 # Ultralytics
 
+[![](/assets/colab.svg)](https://colab.research.google.com/drive/1RAT2vSrvET4wEDd9syeDrgz0KBUDQAR1?usp=sharing)
+
 [Ultralytics](https://github.com/ultralytics/ultralytics) YOLOv8 是一款尖端、最先进的 （SOTA） 模型，它建立在以前 YOLO 版本的成功基础上，并引入了新功能和改进，以进一步提高性能和灵活性。YOLOv8 设计为快速、准确且易于使用，使其成为各种对象检测和跟踪、实例分割、图像分类和姿态估计任务的绝佳选择。
 
 ![ultralytics](/assets/ig-ultralytics.png)