AIEBootcamp/09_Finetuning_Embeddings/Fine_tuning_Embedding_Models_for_RAG_using_RAGAS.ipynb at main · apatti/AIEBootcamp
AI Engineering bootcamp. Contribute to apatti/AIEBootcamp development by creating an account on GitHub.
transformerlab/transformerlab-app: Open Source Application for Advanced LLM Engineering: interact, train, fine-tune, and evaluate large language models on your own computer.
Open Source Application for Advanced LLM Engineering: interact, train, fine-tune, and evaluate large language models on your own computer. - transformerlab/transformerlab-app
Alex Strick van Linschoten - How to think about creating a dataset for LLM finetuning evaluation
I summarise the kinds of evaluations that are needed for a structured data generation task.
Understanding RAG vs Fine-Tuning
Discover the key differences between RAG and fine-tuning, what each approach can bring, and how to choose the right AI approach for your business goals.
An Engineer's Guide to Fine-Tuning LLMs, Part 2: The Execution Playbook
A deep dive into the methods, fine-tuning pipeline, and operational risks of building specialised models.
LoRA Hyperparameters Guide | Unsloth Documentation
Best practices for LoRA hyperparameters and how they affect the fine-tuning process.
Multi-Teacher On-Policy Distillation: A New Post-Training Primitive | Notion
How frontier AI labs use multi-teacher on-policy distillation to merge capabilities, recover from RL forgetting, and scale post-training across MiMo-V2-Flash, GLM-5, Nemotron-Cascade 2, and DeepSeek-V4.
Supervised Fine-Tuning · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Fine-tuning LLMs Guide | Unsloth Documentation
Learn all the basics and best practices of fine-tuning. Beginner-friendly.