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Prompt

I am building a library of prompts to use for evaluating LLMs so that I can identify which will be the most helpful for the specific use-cases I'm targeting. To begin, I'm developing a repository of evaluation prompts: prompts specifically written to compare the capabilities of different LLMs. I would be interested in knowing about the existing frameworks that I can use for this purpose: both SaaS tools built for this and frameworks that I can self-host. I am aiming to streamline the process of selecting the perfect model for a specific recurrent job.

Output

To help streamline the process of evaluating and comparing LLMs for specific use-cases, here are some existing frameworks and SaaS tools that can assist in building your repository of prompts for model assessment:

SaaS Tools for Evaluating LLMs:

  1. OpenAI Playground: Provides a flexible interface for testing prompts across different GPT models with adjustable parameters.
  2. Hugging Face Inference API: Offers access to a variety of models through a unified interface, including comparison tools.
  3. Scale AI: Features a comprehensive platform for LLM evaluations, allowing comparisons and fine-tuning for specific tasks.

Self-Hosted Frameworks:

  1. EleutherAI's LM Evaluation Harness: A framework for evaluating language models on multiple benchmarks with customization options.
  2. GitHub Link
  3. BIG-bench: A collaborative benchmark for evaluating LLMs across diverse tasks.
  4. GitHub Link
  5. OpenPrompt: A prompt-based learning framework that allows model evaluation across tasks, useful for building customized prompt libraries.
  6. GitHub Link

Considerations:

These tools can help automate the process of testing, gathering results, and refining prompts for your targeted tasks. Creating custom evaluation pipelines will make it easier to determine the best model for recurrent jobs.

The above text was generated by a large language model (LLM) and its accuracy has not been validated. This page is part of 'LLMs-on-LLMs,' a Github repository by Daniel Rosehill which explores how curious humans can use LLMs to better their understanding of LLMs and AI. However, the information should not be regarded as authoritative and given the fast pace of evolution in LLM technology will eventually become deprecated. This footer was added at 16-Nov-2024.