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Hey, thanks so much for all the great work with PyPi!
Project description
bitsandbytes was started 1.5 years ago to make the research code of deep learning researcher Tim Dettmers accessible for other researchers and the broad public. By now it has become immensely popular and helps greatly in the effort to democratize AI. The library makes large language model inference and training more accessible by dramatically reducing memory consumption with 8-bit optimizers and k-bit quantization.
8-bit optimizers uses block-wise quantization to maintain 32-bit performance at a small fraction of the memory cost.
LLM.Int() or 8-bit quantization enables large language model inference with only half the required memory and without any performance degradation. This method is based on vector-wise quantization to quantize most features to 8-bits and separately treating outliers with 16-bit matrix multiplication.
QLoRA or 4-bit quantization enables large language model training with several memory-saving techniques that don't compromise performance. This method quantizes a model to 4-bits and inserts a small set of trainable low-rank adaptation (LoRA) weights to allow training.
Efforts to reduce binary size
We're currently maxing out the 100MB in every release. The issue is that we support lot's of CUDA versions, each with "fat binaries" that support many compute capabilities.
We've evaluated how to cut down binary size and reduced the CC and CUDA versions supported relative to prior releases, with this build matrix being the result.
Overall, we're very conscious of the size of our package, but we're always scraping at the 100MB. We'll keep focusing on keeping the binaries as small as technically possible, but it would be great to have some headroom at our disposal if we need, so we don't get blocked by this in the wrong moment.
Hey @Titus-von-Koeller 👋
I've set the upload limit for bitsandbytes to 300 MB on PyPI and TestPyPI. Please be mindful of the frequency of releases at that size.
Have a nice week 🚀
Can you see how close we are to reaching the maximum total data volume for all releases combined? We're a bit afraid that we're already close to that limit based on our estimates, but somehow couldn't find that info in our PyPi view.
Could you increase that as well and let us know where we're currently at, please?
Project URL
https://pypi.org/project/bitsandbytes
Does this project already exist?
New Limit
300 MiB
Update issue title
Which indexes
PyPI, TestPyPI
About the project
Hey, thanks so much for all the great work with PyPi!
Project description
bitsandbytes was started 1.5 years ago to make the research code of deep learning researcher Tim Dettmers accessible for other researchers and the broad public. By now it has become immensely popular and helps greatly in the effort to democratize AI. The library makes large language model inference and training more accessible by dramatically reducing memory consumption with 8-bit optimizers and k-bit quantization.
Efforts to reduce binary size
We're currently maxing out the 100MB in every release. The issue is that we support lot's of CUDA versions, each with "fat binaries" that support many compute capabilities.
Reasons for the request
Overall, we're very conscious of the size of our package, but we're always scraping at the 100MB. We'll keep focusing on keeping the binaries as small as technically possible, but it would be great to have some headroom at our disposal if we need, so we don't get blocked by this in the wrong moment.
cc @matthewdouglas @younesbelkada
Code of Conduct
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