LLMs

OpenGPTs

This is an open source effort to create a similar experience to OpenAI's GPTs. It builds upon LangChain, LangServe and LangSmith. OpenGPTs gives you more control, allowing you to configure:

• The LLM you use (choose between the 60+ that LangChain offers)


• The prompts you use (use LangSmith to debug those)


• The tools you give it (choose from

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TorchMultimodal (Beta Release)

Introduction

TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale. It provides:

• A repository of modular and composable building blocks (models, fusion layers, loss functions, datasets and utilities).


• A repository of examples that show how to combine these building

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The next-generation command line.

The source of truth for your team’s secrets, scripts, and SSH credentials.

How enterprises are using open source LLMs: 16 examples.

Many use Llama-2: Brave, Wells Fargo, IBM, The Grammy Awards, Perplexity, Shopify, LyRise, Niantic....

Quote: “A lot of customer are asking themselves: Wait a second, why am I paying for super large model that knows very little about my business? Couldn’t I just use one of these open-source... See more

Clean & curate your data with LLMs

databonsai is a Python library that uses LLMs to perform data cleaning tasks.

Features

• Suite of tools for data processing using LLMs including categorization, transformation, and extraction


• Validation of LLM outputs


• Batch processing for token savings


• Retry logic with exponential backoff for handling rate limits and

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To do this, we employ a technique known as AI-assisted evaluation, alongside traditional metrics for measuring performance. This helps us pick the prompts that lead to better quality outputs, making the end product more appealing to users. AI-assisted evaluation uses best-in-class LLMs (like GPT-4) to automatically critique how well the AI's... See more

When we deliver a model we make sure we don't reach X seconds of latency in our API. Before even going into performance of LLMs for classification, I can tell you that with the current available tech they are just infeasible.

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LinuxSpinach

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5h ago

^ this. And especially classification as a task, because businesses don’t want to pay llm... See more

The exact metrics we use depend on the application — our main goal is to understand how users use the feature and quickly make improvements to better meet their needs. For internal applications, this might mean measuring efficiency and sentiment. For consumer-facing applications, we similarly focus on measures of user satisfaction - direct user... See more