LLM: From Playgrounds to Production-Ready Pipelines
Explore the journey from LLM playgrounds to enterprise-scale production pipelines, addressing challenges and leveraging MLOps infrastructure for cutting-edge models.
Document Similarity: Langchain, Ollama Mistral 7B, and Chroma in Spanish
Aprende a clasificar documentos usando Langchain, Ollama con Mistral 7B y Chromadb para análisis de similitud en español.
Prompt Engineering: Mistral 7B Techniques for Instruction Creation
Explora técnicas avanzadas de ingeniería de prompts como Zero Shot, Few Shot y Chain of Thought utilizando GPT-3.5 Turbo y Mistral 7B para mejorar tus habilidades en machine learning.
Prompt Engineering: Introducción con OpenAI GPT-4, GPT-3.5 Turbo y Mistral 7B en Español
Explora técnicas de ingeniería de prompts con GPT-4, GPT-3.5 Turbo y Mistral 7B. Aprende a optimizar interacciones con modelos de lenguaje para obtener resultados más precisos y útiles.
MLOps MLflow: Fine-Tuning Mistral 7B con PEFT y QLora - Español
Aprende a ajustar Mistral 7B utilizando técnicas avanzadas como PEFT y QLora, integrando MLflow para un seguimiento eficiente del proceso de fine-tuning.
Prompt Engineering Techniques with Mistral 7B Instruct for Data Science and Machine Learning
Explore prompt engineering techniques using Mistral 7B Instruct, including zero-shot, few-shot, CoT, and RAG. Learn to craft effective prompts for enhanced machine learning outcomes.
Scaling LLM Inference - AWS Inferentia Meets Ray Serve on EKS
Discover how to build scalable, cost-effective LLM inference infrastructure using Ray Serve and AWS Inferentia on Amazon EKS, optimizing deployment of models like Llama2 and Mistral-7B.
Mistral 7B: Architecture, Performance and Implementation Guide
Dive into Mistral 7B's implementation, exploring grouped-query attention, efficient GPU usage, and hands-on demonstrations for running advanced language models on local hardware.
Zephyr 7B Beta - Comparing a 7B LLM with 70B Models
Explore Zephyr 7B Beta's performance against larger models through paper review and hands-on Google Colab tutorial. Learn setup, prompting, and practical applications in math, coding, and data tasks.
Fine-Tuning a Local Mistral 7B Model - Step-by-Step Guide
Step-by-step guide to fine-tuning a Mistral 7B model locally, covering dataset creation, conversion, uploading, fine-tuning, model conversion, and testing, with practical demonstrations and insights.
Data Curation for Open Source LLM Fine-Tuning
Explore data curation challenges and strategies for fine-tuning open source LLMs, focusing on dataset quality and iteration techniques for improved results.
Local LLM Fine-tuning on Mac (M1 16GB) Using QLoRA and MLX
Fine-tune a local LLM on M1 Mac using MLX and QLoRA. Adapt Mistral 7b to respond like you to YouTube comments, with step-by-step guidance and code examples.
Document Similarity: Langchain, Ollama Mistral 7B, and Chroma for Machine Learning and Data Science
Explore document similarity using Langchain, Ollama with Mistral 7B or LLama 2, and Chromadb as VectorStore for machine learning and data science applications.
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.
Fine-Tuning Self-Rewarding Language Models with Mistral 7B
Dive into implementing Meta's Self-Rewarding Language Model with Mistral 7B, covering fine-tuning techniques, data preparation, prompt generation, and practical demonstrations.
Prompt Engineering: OpenAI, GPT-4, and Mistral 7B Basics Introduction
Explore prompt engineering basics with GPT-4, GPT-3.5 Turbo, and Mistral 7B through practical examples and hands-on demonstrations.
GPT-4 vs Open Source LLMs: Epic Rap Battles Test Creativity with AutoGen
Witness open-source LLMs battle GPT4-Turbo in freestyle rap, showcasing linguistic creativity. Compare Wizard LM 70B, Orca-2 13B, and Mistral 7B against the advanced benchmark.
Full Fine-Tuning vs LoRA and QLoRA - Comparison and Best Practices
Explore full fine-tuning vs (Q)LoRA techniques, comparing VRAM usage, training time, and quality. Learn parameter selection, tips for QLoRA, and step-by-step guidance for TinyLlama and Mistral 7B fine-tuning.