Fine-Tune Gemma 3: A Step-by-Step Guide With Financial Q&A Dataset
Fine-tune the new Gemma model using the finance reasoning dataset to improve its accuracy and adopt the style of the dataset.
Mar 21, 2025 · 11 min read
Learn to develop large language models (LLMs) with PyTorch and Hugging Face, using the latest deep learning and NLP techniques.
Fine-tune Llama for custom tasks using TorchTune, and learn techniques for efficient fine-tuning such as quantization.
Unlock more advanced AI applications, like semantic search and recommendation engines, using OpenAI's embedding model!
[
See More
](https://www.datacamp.com/category/artificial-intelligence)
Related
Learn how to run inference on GPUs/TPUs and fine-tune the latest Gemma 7b-it model on a role-play dataset.
This is a simple guide to fine-tuning Gemma 2 9B-It on patient-doctor conversations and converting the model into GGUF format so that it can be used locally with the Jan application.
Learn to infer and fine-tune LLMs with TPUs and implement model parallelism for distributed training on 8 TPU devices.
Discover Microsoft's new LLM series and boost your model's accuracy from 65% to 86% by fine-tuning it on the E-commerce classification dataset.
Learn how fine-tuning large language models (LLMs) improves their performance in tasks like language translation, sentiment analysis, and text generation.
Learn how to use PaliGemma 2 Mix to build an AI-powered bill scanner and spending analyzer that extracts and categorizes expenses from receipts.