官方说明3 个来源MCP 服务3 天前
Hugging Face Diffusion Models Course
Python materials for the online course on diffusion models by
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- 来源明细
- 收录自 steven2358/awesome-generative-ai 榜单（我们从中收集的条目之一） · 条目类型：MCP 服务
- 收录与活跃
- 收录于 2026-10-14 · 最近见到 2026-10-16 · 共见到 4 次 · 被 3 个来源列出
- 评分构成
- 综合分 303 · 3 个来源 · mcp
常见问题（答案都来自我们的记录）
怎么安装？
我们【没有】从该仓库取到安装命令（我们的 install 覆盖率只有约 4%）。请看它的 README 或 releases 页。
它适合谁 / 用来做什么？
我们把它归在这些标签下: MCP 服务。标签来自条目自身，不是我们强加的分类。
谁维护它、还在更新吗？
我们收录于 2026-10-14；最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记
Hugging Face Diffusion Models Course
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
In this free course, you will:
- 👩🎓 Study the theory behind diffusion models
- 🧨 Learn how to generate images and audio with the popular 🤗 Diffusers library
- 🏋️♂️ Train your own diffusion models from scratch
- 📻 Fine-tune existing diffusion models on new datasets
- 🗺 Explore conditional generation and guidance
- 🧑🔬 Create your own custom diffusion model pipelines
Register via the **signup form** and then join us on **Discord** to get the conversations started. Instructions on how to join specific categories/channels **are here.**
Syllabus
| 📆 Publishing date | 📘 Unit | 👩💻 Hands-on |
|---------------|----------------------------------------------------------|----------------------------------------------------------------------------------------------------------|
| November 28, 2022 | An Introduction to Diffusion Models| Introduction to Diffusers and Diffusion Models From Scratch |
| December 12, 2022 | Fine-Tuning and Guidance | Fine-Tuning a Diffusion Model on New Data and Adding Guidance |
| December 21, 2022 | Stable Diffusion | Exploring a Powerful Text-Conditioned Latent Diffusion Model |
| January 2023 (TBC) | Doing More with Diffusion | Advanced Techniques to Take Diffusion Further |
More information coming soon!
Prerequisites
- Good skills in Python 🐍
- Basics in Deep Learning and Pytorch
If it's not the case yet, you can check these free resources:
- Python: https://www.udacity.com/course/introduction-to-python--ud1110
- Intro to Deep Learning with PyTorch: https://www.udacity.com/course/deep-learning-pytorch--ud188
- PyTorch in 60 min: https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html
FAQ
**Is this class free?**
Yes, totally free 🥳.
**Do I need to have a Hugging Face account to follow the course?**
Yes, to push your custom models and pipelines to the hub, you need an account (it's free) 🤗.
You can create one here 👉 https://huggingface.co/join
**What’s the format of the class?**
The course will consist of at least **4 Units.** More will be added as time goes on, on topics like diffusion for audio.
Each unit consists of some theory and background alongside one or more hands-on notebooks. Some units will also contain suggested projects and we'll have competitions and swag for the best pipelines and demos (more details TDB).
🌎 Languages and translations
In this free course, you will:
- 👩🎓 Study the theory behind diffusion models
- 🧨 Learn how to generate images and audio with the popular 🤗 Diffusers library
- 🏋️♂️ Train your own diffusion models from scratch
- 📻 Fine-tune existing diffusion models on new datasets
- 🗺 Explore conditional generation and guidance
- 🧑🔬 Create your own custom diffusion model pipelines
Register via the **signup form** and then join us on **Discord** to get the conversations started. Instructions on how to join specific categories/channels **are here.**
Syllabus
| 📆 Publishing date | 📘 Unit | 👩💻 Hands-on |
|---------------|----------------------------------------------------------|----------------------------------------------------------------------------------------------------------|
| November 28, 2022 | An Introduction to Diffusion Models| Introduction to Diffusers and Diffusion Models From Scratch |
| December 12, 2022 | Fine-Tuning and Guidance | Fine-Tuning a Diffusion Model on New Data and Adding Guidance |
| December 21, 2022 | Stable Diffusion | Exploring a Powerful Text-Conditioned Latent Diffusion Model |
| January 2023 (TBC) | Doing More with Diffusion | Advanced Techniques to Take Diffusion Further |
More information coming soon!
Prerequisites
- Good skills in Python 🐍
- Basics in Deep Learning and Pytorch
If it's not the case yet, you can check these free resources:
- Python: https://www.udacity.com/course/introduction-to-python--ud1110
- Intro to Deep Learning with PyTorch: https://www.udacity.com/course/deep-learning-pytorch--ud188
- PyTorch in 60 min: https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html
FAQ
**Is this class free?**
Yes, totally free 🥳.
**Do I need to have a Hugging Face account to follow the course?**
Yes, to push your custom models and pipelines to the hub, you need an account (it's free) 🤗.
You can create one here 👉 https://huggingface.co/join
**What’s the format of the class?**
The course will consist of at least **4 Units.** More will be added as time goes on, on topics like diffusion for audio.
Each unit consists of some theory and background alongside one or more hands-on notebooks. Some units will also contain suggested projects and we'll have competitions and swag for the best pipelines and demos (more details TDB).
🌎 Languages and translations
- 来源
- awesome · https://github.com/huggingface/diffusion-models-class
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