Explores building enterprise applications using Azure OpenAI and Microsoft's data platform for secure, integrated AI solutions.
A technical guide on deploying Hugging Face's IDEFICS visual language models (9B & 80B parameters) to Amazon SageMaker using the LLM DLC.
A benchmark analysis of deploying Meta's Llama 2 models on Amazon SageMaker using Hugging Face's LLM Inference Container, evaluating cost, latency, and throughput.
A technical guide on fine-tuning the massive Falcon 180B language model using DeepSpeed ZeRO, LoRA, and Flash Attention for efficient training.
An introduction to Semantic Kernel's Planner, a tool for automatically generating and executing complex AI tasks using plugins and natural language goals.
Guide to deploying open-source LLMs like BLOOM and Open Assistant to Amazon SageMaker using Hugging Face's new LLM Inference Container.
Explores how mixed-precision training techniques can speed up large language model training and inference by up to 3x, reducing memory use.
Exploring mixed-precision techniques to speed up large language model training and inference by up to 3x without losing accuracy.
A curated list of open-source Large Language Models (LLMs) available for commercial use, including community-contributed updates and details.
A technical tutorial on fine-tuning a 20B+ parameter LLM using PyTorch FSDP and Hugging Face on Amazon SageMaker's multi-GPU infrastructure.
Explains parameter-efficient finetuning methods for large language models, covering techniques like prefix tuning and LLaMA-Adapters.
A guide to parameter-efficient finetuning methods for large language models, covering techniques like prefix tuning and LLaMA-Adapters.
Introduces IGEL, an instruction-tuned German large language model based on BLOOM, for NLP tasks like translation and QA.
Guide to finetuning large language models on a single GPU using gradient accumulation to overcome memory limitations.
A guide to finetuning large language models like BLOOM on a single GPU using gradient accumulation to overcome memory limits.
A technical guide on fine-tuning the large FLAN-T5 XXL model efficiently using LoRA and Hugging Face libraries on a single GPU.
Guide to fine-tuning the large FLAN-T5 XXL model using Amazon SageMaker managed training and DeepSpeed for optimization.
Argues against the 'lossy compression' analogy for LLMs like ChatGPT, proposing instead that they are simulators creating temporary simulacra.
A curated reading list of key academic papers for understanding the development and architecture of large language models and transformers.
A curated reading list of key academic papers for understanding the development and architecture of large language models and transformers.
