baichuan and baichuan2 finetuning and alpaca finetuning
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Updated
Apr 21, 2024 - Python
baichuan and baichuan2 finetuning and alpaca finetuning
A bash scripting assistant that helps you automate tasks. Powered by a streamlit chat interface, A finetuned nl2bash model generates bash code from natural language descriptions provided by the user
This model is a fine-tuned model based on the "TinyPixel/Llama-2-7B-bf16-sharded" model and "timdettmers/openassistant-guanaco" dataset
A Multimodal Approach to Convert Book Summaries into Artistic Book Covers
perform deduplication on FLAN v2 dataset & Finetune LLaMa3 using this dataset
Lite Korean language model
Implementation for fine-tuning a Falcon-7b model using QLoRA on the Spider dataset. The repository focuses on the task of converting natural language questions into SQL commands.
Kickstart with LLMs
Our project addresses the challenge of multi-document summarization with Large Language Models (LLMs), which are constrained by token length limitations. We propose a novel approach that combines the strengths of LLMs and Maximal Marginal Relevance (MMR).
Code for fine-tuning Llama2 LLM with custom text dataset to produce film character styled responses
llama-2 model finetuned to generate docker commands
An LLM challenge to (i) fine-tune pre-trained HuggingFace transformer model to build a Code Generation language model, and (ii) build a retrieval-augmented generation (RAG) application using LangChain
This project fine-tunes large language models (LLMs) for text-based recommendations, using a novel prompt mechanism to improve accuracy and user satisfaction. It demonstrates efficient model adaptation with diverse datasets, leveraging advanced libraries and techniques for optimal performance.
qwen-1.5-1.8B sentiment analysis with prompt optimization and qlora fine-tuning
Fine-tuned FLAN T-5 using Instruction Fine-Tuning (Full), LoRA-based PEFT, and RLHF with PPO
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