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Chatbot built using Flask and the OpenAI GPT-3.5 turbo model. The chatbot allows users to interact with a language model powered by GPT-3.5 turbo and get responses based on their input.
Exploring the potential of fine-tuning Large Language Models (LLMs) like Llama2 and StableLM for medical entity extraction. This project focuses on adapting these models using PEFT, Adapter V2, and LoRA techniques to efficiently and accurately extract drug names and adverse side-effects from pharmaceutical texts
Pre-Training and Fine-Tuning transformer models using PyTorch and the Hugging Face Transformers library. Whether you're delving into pre-training with custom datasets or fine-tuning for specific classification tasks, these notebooks offer explanations and code for implementation.
This repository implements a self-updating RAG (Retrograde Autoregressive Generation) model. It leverages Wikipedia for factual grounding and can fine-tune itself when information is unavailable. This allows the model to continually learn and adapt, offering a dynamic and informative response.
Develop a Romanian legal domain Large Language Model (LLM) using pre-trained model and fine-tuning on legal texts. The fine-tuned model is available on Hugging Face.
The MistralAI API wrapper for Delphi utilizes the various advanced models developed by Mistral to provide robust capabilities for chat interactions, string embeddings, and precise code generation with Codestral.