An innovative library for efficient LLM inference via low-bit quantization

Collection of resources for finetuning Large Language Models (LLMs).

Distributed Reinforcement Learning for LLM Fine-Tuning with multi-GPU utilization

Sustain-LC is a benchmarking environment for traditional and reinforcement learning based controls as well as LLM based control

A sacred space for heartfelt conversations, where wisdom flows freely and memories gently fade like whispers at sunset.

Análise Avançada de Dados com Causalidade e Aprendizado por Reforço

FlowerTune LLM on Coding Dataset

The Personal Knowledge Graph You Didn’t Know You Already Wrote

ARC-Test-Time-Training (ARC-TTT)

Chaining thoughts and LLMs to learn DNA structural biophysics

FlowerTune LLM on Medical Dataset

Clone your Discord friends with AI!

FlowerTune LLM on NLP Dataset

Comparing QLoRA, Prompt & Prefix Tuning on Mistral-7B for medical instruction-following

Django implementation of CodeBERT for detecting vulnerable code.

Schematic Blueprint for Finetuning LLM (e.g. Qwen or Llama) for text classification using LORA. Output model can have original or modified head (e.g. for SequenceClassification).

This repository contains all the notebooks, resources, and documentation used to develop and evaluate models for the Automated Essay Scoring (AES) Kaggle competition. The project aims to build an open-source solution for automated essay evaluation to support educators and provide timely feedback to students.

Showcase a fine-tuned model trained for a specific task or audience.

Implemented and fine-tuned BERT for a custom sequence classification task, leveraging LoRA adapters for efficient parameter updates and 4-bit quantization to optimize performance and resource utilization.