Opencompass Alternatives

Similar projects and alternatives to opencompass based on common topics and language

evals

49 13,878 9.4 Python opencompass VS evals

Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
lm-evaluation-harness

34 4,957 9.9 Python opencompass VS lm-evaluation-harness

A framework for few-shot evaluation of language models.
InfluxDB

www.influxdata.com sponsored

Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
deepeval

22 1,769 9.9 Python opencompass VS deepeval

The LLM Evaluation Framework
promptbench

4 1,969 9.2 Python opencompass VS promptbench

A unified evaluation framework for large language models
bocoel

1 255 9.5 Python opencompass VS bocoel

Bayesian Optimization as a Coverage Tool for Evaluating LLMs. Accurate evaluation (benchmarking) that's 10 times faster with just a few lines of modular code.
vibraniumdome

1 41 9.3 Python opencompass VS vibraniumdome

Discontinued LLM Security Platform.
CommonGen-Eval

2 79 7.8 Python opencompass VS CommonGen-Eval

Evaluating LLMs with CommonGen-Lite
WorkOS

workos.com sponsored

The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better opencompass alternative or higher similarity.

Suggest an alternative to opencompass

opencompass reviews and mentions

Posts with mentions or reviews of opencompass. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-13.

Show HN: Times faster LLM evaluation with Bayesian optimization
6 projects | news.ycombinator.com | 13 Feb 2024

Fair question.
Evaluate refers to the phase after training to check if the training is good.
Usually the flow goes training -> evaluation -> deployment (what you called inference). This project is aimed for evaluation. Evaluation can be slow (might even be slower than training if you're finetuning on a small domain specific subset)!
So there are [quite](https://github.com/microsoft/promptbench) [a](https://github.com/confident-ai/deepeval) [few](https://github.com/openai/evals) [frameworks](https://github.com/EleutherAI/lm-evaluation-harness) working on evaluation, however, all of them are quite slow, because LLM are slow if you don't have infinite money. [This](https://github.com/open-compass/opencompass) one tries to speed up by parallelizing on multiple computers, but none of them takes advantage of the fact that many evaluation queries might be similar and all try to evaluate on all given queries. And that's where this project might come in handy.