🤗 Hugging Face Cheatsheet
5-Page Hugging Face Ecosystem Cheatsheet
Abonia Sojasingarayar
AI and ML Insights: AI Magazine
Latest episodes
📚 E-Book - From Research to Production - Industrializing NLP and Large Language Models
E-book release : From Research to Production - Industrializing NLP and Large Language Model
CHAPTER 7 - Mastering LLMOps: Operationalizing Large Language Models in the Generative AI Landscape
Streamlining Generative AI Workflows with LLMOps
Chapter 3 - Advanced Language Modeling and Transformers
Diving into language models, sequence architectures, and transformer-based innovations
Chapter 2 - Traditional and Modern Text Representation Techniques
Exploring foundational and advanced methods for representing textual data
Open-Source Vision Language Models (VLMs) in Multimodal AI
Curated List - Open source - Multimodal AI
Chapter 6 - Real-World Applications of RAG and LLMs
Hands-On real time RAG and LLM application
Chapter 5 - Fine-tuning, Adaptation, Evaluation, and Debugging of LLMs
Fine-tuning, Adaptation, Evaluation, and Debugging of LLMs
Chapter 4 - Introduction to Large Language Models
Overview of LLMs
Chapter 1 - Introduction to NLP
Understanding of NLP and its potential applications
Understanding Kubernetes: Comprehensive Practical Guide
Components, Importance and Advantages
vLLM and PagedAttention: A Comprehensive Overview
Easy, Fast, and Cheap LLM Serving
Summarization with LangChain
Stuff — Map_reduce — Refine
Books on LLM and NLP in 2024
Exploring the Best Books for Understanding and Implementing LLMs in NLP
Deploying a RAG Application in AWS Lambda using Docker and ECR
Lambda — ECR — Docker — LangChain — OpenAI
EDA — Visualize Embeddings of RAG
UMAP — Visualize RAG data — Langchain Chroma HuggingFaceEmbeddings
Build and Deploy LLM Application in AWS
AWS Lambda — BedRock — LangChain
Ollama and LangChain: Run LLMs locally
Run open-source LLM, such as Llama 2,mistral locally
Machine Learning Model Serving Framework
Framework/Server for model serving
LLM Series - Quantization Overview
Enhancing Efficiency While Maintaining Quality