80% faster, 50% less memory, 0% accuracy loss Llama finetuning

• hyperlearn

  4 1,578 0.0 Jupyter Notebook

  2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

  

Sorry about that - I'm super new to pricing and stuff so it might seem off since I'm literally making the plans with my bro as we go along.

If you don't believe the timings, I was the author of Hyperlearn https://github.com/danielhanchen/hyperlearn which makes ML faster - I also listed the papers which cite the algos.

I also used to work at NVIDIA making TSNE 2000x faster on GPUs and some other algos like Randomized SVD, sparse matrix multiplies etc.

If you have any suggestions on a more appropriate pricing strategy - I'm all ears!!

I really don't know much about pricing and the open core model, so I'm making stuff up literally.

• unsloth

  15 7,263 9.4 Python

  Finetune Llama 3, Mistral & Gemma LLMs 2-5x faster with 80% less memory

  

This seems to just be a link to the Unsloth Github repo[0], which in turn is the free version of Unsloth Pro/Max[1]. Maybe the link should be changed?

[0]: https://github.com/unslothai/unsloth

• 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.

  

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