datawhalechina/diy-llm
Covers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack LLM learning | 涵盖预训练数据、分词器、Transformer
- Stars
- 1.5k
- Forks
- 158
- Open issues
- 1
- Last push
- 13d ago
About diy-llm
diy-llm is a free, open-source LLM chat app by datawhalechina, written mainly in Jupyter Notebook. Covers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack LLM learning | 涵盖预训练数据、分词器、Transformer. It has 1.5k GitHub stars and 158 forks, and was last updated 13d ago. GitHub doesn't detect a standard license, so check the repository before using it commercially.
- License
- Not detected
- Language
- Jupyter Notebook
- Stars
- 1,531
- Last update
- 13d ago
- Runs on Mac
- Not stated
- GPU
- Not stated
- Paid API key
- Not stated
- Self-hostable
- Not stated
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diy-llm FAQ
Is diy-llm free?
Yes. diy-llm is open source and free to use. GitHub doesn't detect a standard license, so check the repository before using it commercially.
Does diy-llm run on a Mac?
The project doesn't say. Check its installation guide before you start.
Does diy-llm need a GPU?
The project doesn't state hardware needs. AI models generally run much faster with a GPU.
Is diy-llm still maintained?
Yes. It was last updated 13d ago and has 1 open issues on GitHub.
What are alternatives to diy-llm?
Similar free, open-source tools include self-llm, Open-LLM-VTuber, transformer-explainer, open-webui.