Personalize your generative AI applications with Amazon SageMaker Feature Store | Amazon Web Services
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Personalize your generative AI applications with Amazon SageMaker Feature Store | Amazon Web Services
Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
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SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with LLMs faster and more controllable by co-designing the frontend language and the runtime system.
The core features of SGLang include:
The core features of SGLang include:
- A Flexible Front-End Language : This allows for easy programming of LLM applications with multiple ch
sgl-project • GitHub - sgl-project/sglang: SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with models faster and more controllable.
Nicolay Gerold added
simply accessing LLMs via APIs has limitations. Instead, combining them with other data sources and tools can enable more powerful applications. In this chapter, we will introduce LangChain as a way to overcome LLM limitations and build innovative language-based applications.
Ben Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with LLMs faster and more controllable by co-designing the frontend language and the runtime system.
The core features of SGLang include:
The core features of SGLang include:
- A Flexible Front-End Language : This allows for easy programming of LLM applications with multiple ch
sgl-project • GitHub - sgl-project/sglang: SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with models faster and more controllable.
Nicolay Gerold added
They have a fast jsond ecoding feature with a finite state machine.
We generally lean towards picking more advanced commercial LLMs to quickly validate our ideas and obtain early feedback from users. Although they may be expensive, the general idea is that if problems can't be adequately solved with state-of-the-art foundational models like GPT-4, then more often than not, those problems may not be addressable usin... See more
Developing Rapidly with Generative AI
Nicolay Gerold added
📦 Service Deployment - Ray Serve (https://lnkd.in/eAV-Y6RN)
🧰 Data Transformation - Ray Data (https://lnkd.in/e7wYmenc)
🔌 LLM Integration - AIConfig (https://lnkd.in/esvH5NQa)
🗄 Vector Database - Weaviate (https://weaviate.io/)
📚 Supervised LLM Fine-Tuning - HuggingFace TLR (https://lnkd.in/e8_QYF-P)
📈 LLM Observability - Weights & Biases Tra... See more
🧰 Data Transformation - Ray Data (https://lnkd.in/e7wYmenc)
🔌 LLM Integration - AIConfig (https://lnkd.in/esvH5NQa)
🗄 Vector Database - Weaviate (https://weaviate.io/)
📚 Supervised LLM Fine-Tuning - HuggingFace TLR (https://lnkd.in/e8_QYF-P)
📈 LLM Observability - Weights & Biases Tra... See more