Bonsai-27B-GGUF
lmstudio-community · Kit
A GGUF conversion of the 27B Bonsai model for LM Studio, with a 3.80 GB Q1_0 language file and a 0.93 GB BF16 vision projector. Tested for text, vision and par…
Collects the notebooks of the Hugging Face Agents Course, covering a dummy agent library, smolagents, LlamaIndex, LangGraph and two bonus units. For learners building AI agents hands-on.
Agents Course Notebooks is a kit in the Education category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.
pip install -U huggingface_hub hf download agents-course/notebooks
This repository holds the hands-on notebooks that go with the Hugging Face Agents Course. The index lists 16 entries, mostly Jupyter notebooks and one Python script, grouped by unit. They cover a dummy agent library, three agent frameworks and two bonus units.
It suits learners who follow the Agents Course and want the practice files, and developers who want to compare how smolagents, LlamaIndex and LangGraph build agents.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| Education | Learners on the course | Open the notebook for each unit as they study | Work through the Code Agents notebook |
| Software | Developers choosing a framework | Read the same ideas in three frameworks | Compare the Tools notebooks for smolagents and LlamaIndex |
| Training | Teachers running a workshop | Use the units as class exercises | Assign the Mail Sorting notebook |
People who want a ready-made agent product can skip it, since these are teaching notebooks.
| Use case | Who | What they get back |
|---|---|---|
| Learn the basics | Beginners | A dummy agent library notebook in Unit 1 |
| Try a framework | Developers | Notebooks for smolagents, LlamaIndex or LangGraph in Unit 2 |
| Go further | Advanced learners | Bonus notebooks on tuning Gemma and on monitoring agents |
You need these first:
pip install -U huggingface_hub hf download agents-course/notebooks
Follow the course units in order and open the matching notebook from the index. The card text gives no run steps beyond the download, so follow the course pages for details.
| Tool | What it does |
|---|---|
| Unit 1 | The Dummy Agent Library notebook |
| Unit 2.1 smolagents | Code Agents, Multi-agent, Retrieval Agents, Tool Calling Agents, Tools and Vision Agents notebooks, plus a Vision Web Browser script |
| Unit 2.2 LlamaIndex | Agents, Components, Tools and Workflows notebooks |
| Unit 2.3 LangGraph | Agent and Mail Sorting notebooks |
| Bonus Unit 1 | A notebook on Gemma SFT and thinking function calls |
| Bonus Unit 2 | A notebook on monitoring and evaluating agents |
A learner finishing Unit 2.3 opens the Mail Sorting notebook from the LangGraph group to practice building an agent that sorts mail. The notebook is the hands-on part of that unit.
An agent is a program where a language model chooses actions and uses tools. A first small step is to open the Unit 1 notebook, which builds a dummy agent library, before trying a framework.
Unit 2 repeats the agent idea in three frameworks, so you can see what each one makes easy. The bonus units go further, with supervised fine-tuning of Gemma for function calling and with ways to monitor and evaluate agents.
Collects the notebooks of the Hugging Face Agents Course, covering a dummy agent library, smolagents, LlamaIndex, LangGraph and two bonus units. For learners building AI agents hands-on.
Made by agents-course on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.
What it is: This repository holds the hands-on notebooks that go with the Hugging Face Agents Course. The index lists 16 entries, mostly Jupyter notebooks and one Python script, grouped by unit. They cover a dummy agent library, three agent frameworks and two bonus units.
Who it suits: It suits learners who follow the Agents Course and want the practice files, and developers who want to compare how smolagents, LlamaIndex and LangGraph build agents.
Industry | Who uses it | How they use it | Example
Education | Learners on the course | Open the notebook for each unit as they study | Work through the Code Agents notebook
Software | Developers choosing a framework | Read the same ideas in three frameworks | Compare the Tools notebooks for smolagents and LlamaIndex
Training | Teachers running a workshop | Use the units as class exercises | Assign the Mail Sorting notebook
People who want a ready-made agent product can skip it, since these are teaching notebooks.
Where to use it:
Use case | Who | What they get back
Learn the basics | Beginners | A dummy agent library notebook in Unit 1
Try a framework | Developers | Notebooks for smolagents, LlamaIndex or LangGraph in Unit 2
Go further | Advanced learners | Bonus notebooks on tuning Gemma and on monitoring agents
How to set it up: You need these first:
pip install -U huggingface_hub
hf download agents-course/notebooks
How to use it: Follow the course units in order and open the matching notebook from the index. The card text gives no run steps beyond the download, so follow the course pages for details.
Tool | What it does
Unit 1 | The Dummy Agent Library notebook
Unit 2.1 smolagents | Code Agents, Multi-agent, Retrieval Agents, Tool Calling Agents, Tools and Vision Agents notebooks, plus a Vision Web Browser script
Unit 2.2 LlamaIndex | Agents, Components, Tools and Workflows notebooks
Unit 2.3 LangGraph | Agent and Mail Sorting notebooks
Bonus Unit 1 | A notebook on Gemma SFT and thinking function calls
Bonus Unit 2 | A notebook on monitoring and evaluating agents
Example: A learner finishing Unit 2.3 opens the Mail Sorting notebook from the LangGraph group to practice building an agent that sorts mail. The notebook is the hands-on part of that unit.
For newcomers and experts: An agent is a program where a language model chooses actions and uses tools. A first small step is to open the Unit 1 notebook, which builds a dummy agent library, before trying a framework.
Unit 2 repeats the agent idea in three frameworks, so you can see what each one makes easy. The bonus units go further, with supervised fine-tuning of Gemma for function calling and with ways to monitor and evaluate agents.
Start with the Dummy Agent Library in Unit 1
Pick a framework in Unit 2
Build agents with tools in its notebooks
Try the bonus units on tuning and monitoring
Good to know:
Download its files with Hugging Face's command line:
pip install -U huggingface_hub
hf download agents-course/notebooks
Then follow the usage in its model card. Nothing in this kit runs by itself.
README.md 5 KB
Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search and on Trendshift. Mindket doesn’t write or check them. Open one to read it where it was posted.
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