llm-course
This project is a training curriculum for those who wish to gain entry into the Big Language Models (LLM) field. Starting from the basics of mathematics and Python, the model includes fine-tuning and Colab notebooks covering application development processes.
mlabonne · AI / LLM / RAG
Common commercial products in this category: ChatGPT, Claude, Gemini
- Using ready-made notebooks on Google Colab, you can fine-tune models.
- With the AutoQuant notepad, you can quantify models in GGUF, GPTQ, EXL2, AWQ and HQQ formats, combining them with LazyMergekit with one click.
- By following the training curriculum, you can design and publish LLM-based applications.
- • No published release
- • NeutralGitHub Issue
Pls help, stuck with AutoGGUF
“I tried to make ggufs of different models (one that was already available and one which I made using the lazymergekit). I always get the same error how ever. It's this one (I edited the model name out but it happens with both I tested. They are Mistral 7b based ones): ```…”
- • NeutralGitHub Issue
LazyMergeKit - Tensor model.final_layernorm.weight required but not present in model ...
“Hi there I'm trying to merge Phi-2 models using the following config: `MODEL_NAME = "..." yaml_config = """ models: - model: microsoft/phi-2 # no parameters necessary for base model - model: rhysjones/phi-2-orange parameters: density: 0.5 weight: 0.5 - model:…”
Verified against README · Oct 26, 2026 · source
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