HEMANGANI/Fine-Tuning-LLM-for-QA
Fine-Tuning Large Language Models for Question Answering
This project helps you build a system that can automatically answer questions from a given document or text. You feed it a collection of text passages and a question, and it extracts the most relevant answer directly from the text. This is designed for anyone who needs to quickly find specific information within large amounts of written material, such as researchers, analysts, or customer support specialists.
No commits in the last 6 months.
Use this if you need an automated way to pull precise answers out of long documents or articles without manually reading through them.
Not ideal if you need a system that can generate creative answers, summarize information, or answer questions requiring external knowledge not present in the provided text.
Stars
8
Forks
1
Language
Jupyter Notebook
License
—
Category
Last pushed
Feb 13, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/HEMANGANI/Fine-Tuning-LLM-for-QA"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
OptimalScale/LMFlow
An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
adithya-s-k/AI-Engineering.academy
Mastering Applied AI, One Concept at a Time
jax-ml/jax-llm-examples
Minimal yet performant LLM examples in pure JAX
young-geng/scalax
A simple library for scaling up JAX programs
riyanshibohra/TuneKit
Upload your data → Get a fine-tuned SLM. Free.