LIMA: Less is More for Alignment - Turning Language Models into Chatbots
Explore LIMA, a LLaMa-based model fine-tuned on 1,000 curated prompts, producing impressive responses without user data or RLHF. Discover insights on language model alignment from this innovative approach.
Fine-Tuning LLMs: Helix for Text and Image AI Models
Explore Helix for fine-tuning text and image AI using open-source models. Learn about challenges in creating a fine-tuning service platform from a software infrastructure expert.
Productionizing Health Insurance Appeal Generation - AI in Production
Explore fine-tuning models for health insurance appeals, cloud resource utilization, and on-premises Kubernetes deployment. Learn about unexpected challenges in server setup and graphics card installation.
Fine-Tuning ViT Classifier with Custom Data - Inference for Images and Videos
Fine-tune a ViT model with custom data and perform inference on images and videos. Learn practical techniques for image and video classification using advanced machine learning.
Fine-Tune T5 for Document Classification - Part 1: Creating Dataset with Web Scraping
Personalize Flan-T5 for document classification by creating a custom dataset using web scraping techniques with DuckDuckGo.
Fine-Tuning Flan T5 Base for Document Summarization Using Multi-News Dataset
Fine-tune Flan T5 for document summarization using multi_news dataset. Learn practical implementation with provided notebook and explore variations with other models and datasets.
Fine-Tuning Gemini 1.0 Pro for Text Classification in Vertex AI
Fine-tune Gemini Pro 1.0 for text classification using Google Vertex AI's UI and Python SDK. Learn advanced machine learning techniques for improved model performance.
MLOps: Fine-tuning Mistral 7B with PEFT, QLora, and MLFlow
Fine-tune Mistral 7B using PEFT, QLora, and MLFlow techniques. Master advanced LLM optimization for improved performance and efficiency.
LLMOps: Inference of Fine-Tuned ViT Classifier on CPU with C#
Perform CPU inference on a fine-tuned Vision Transformer using C# and ONNX format for efficient image classification in machine learning projects.
Fine-tuning Llama 2 for Tone or Style Using Shakespeare Dataset
Fine-tune Llama 2 for Shakespearean style using custom datasets. Learn LoRA, parameter settings, and inference techniques to adapt language models for specific tones or styles.
Preparing Fine-tuning Datasets with Open Source LLMs
Learn to prepare fine-tuning datasets using open-source LLMs like Llama 2. Explore data preparation scripts, Q&A dataset creation, and API setup for effective model customization.
Chat Fine-Tuning for LLMs - Instruction Format, Datasets, and Implementation
Master LLM instruction fine-tuning techniques, from understanding special tokens to implementing various prompt formats. Gain hands-on experience with datasets and Jupyter lab, culminating in practical chat fine-tuning results.
Embeddings vs Fine-Tuning - Part 3: Unsupervised Fine-Tuning
Explore unsupervised fine-tuning techniques for embeddings, including dataset cleanup, Google Colab implementation, and expert tips for optimal results.
Fine-tuning Multi-modal Video and Text Models
Explore fine-tuning techniques for multi-modal video and text models, covering dataset generation, clipping, querying, and evaluation using IDEFICS 2 and Jupyter Notebooks.
Top Ten Tips for Fine-tuning Large Language Models
Discover ten essential tips for effective fine-tuning of language models, from starting small to advanced techniques like LoRA and preference tuning. Gain practical insights for optimal results.
Simplified Training, Tuning and Deployment of Foundational Models as a Service with Red Hat OpenShift
Simplify end-to-end lifecycle of foundation models using Red Hat OpenShift Data Science. Learn about cloud-native, scalable stack for training, tuning, and inferencing with integrated open-source components.
Lessons From Fine-Tuning Llama-2
Explore insights from fine-tuning Llama-2 for specialized applications. Learn setup, infrastructure, and efficiency techniques to outperform GPT-4 in specific scenarios using Anyscale and Ray.
LLM News: Llama 3.1, Self-Improving Agents, and Recent AI Developments
Explore latest AI advancements: Llama 3.1, self-improving agents, text-to-SQL, multi-LLM systems, and GPT-4 fine-tuning. Stay updated on cutting-edge developments in machine learning and artificial intelligence.
Mistral AI Agents and Fine-tuning Tutorial
Learn to build efficient custom models using Mistral AI's new Agents and Fine-tuning features in this tutorial covering announcements, implementation, and practical applications.
Selecting the Right Large Language Model - A Systematic Approach
Systematic framework for experimenting with and selecting the optimal LLM, considering factors like performance, cost, and specific use case requirements.
Creating Your Own Flux AI Model with LoRA Fine-Tuning
Learn to create and fine-tune a custom Flux AI model using LoRA, including dataset preparation, cost-effective training on Replicate, and generating AI images with your personalized model.