llm-analysis
Latency and Memory Analysis of Transformer Models for Training and Inference
Analyze the speed and memory usage of transformer models during training and when making predictions.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimeLatency and Memory Analysis of Transformer Models for Training and Inference
llm-analysis has 489 stars on GitHub. It has been forked 59 times. llm-analysis is written mainly in Python. It has been in active development since 2023. llm-analysis is available under the Apache-2.0 license. Its main topics are analysis, deep-learning, language-model, language-models.
What is llm-analysis?
Latency and Memory Analysis of Transformer Models for Training and Inference
Is llm-analysis open source?
llm-analysis is an open-source project. It is released under the Apache-2.0 license.
Is llm-analysis free?
Yes. llm-analysis is free and open source — you can use, modify and self-host it.
What license does llm-analysis use?
llm-analysis is available under the Apache-2.0 license.
What language is llm-analysis written in?
llm-analysis is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/cli99-llm-analysis.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.