LocalAIVoiceChat VS cuml

Was following these two projects by someuser on Github which makes similar things possible with Local models. Sending screenshot to openai is expensive , if done every few seconds or minutes.

https://github.com/KoljaB/LocalAIVoiceChat

While the below one uses openai - don't see why it can't be replaced with above project and local mode.

https://github.com/KoljaB/Linguflex

What a coincidence, was just looking something similar for local models and stumbled up on this, his Repo seems full of TTS/STT projects..

https://github.com/KoljaB/LocalAIVoiceChat

Code: If you're curious, want to chip in, or just want to take a look, here's the link to the Github.

sklearn can't, bit take a look at cuML (https://github.com/rapidsai/cuml ). It uses the same API as sklearn but executes on GPU.

As a companion to the other comments, I'd like to mention that the RAPIDS library cuML provides GPU-accelerated versions of quite a few of the algorithms mentioned in this thread (HDBSCAN, UMAP, SVM, PCA, {Exact, Approximate} Nearest Neighbors, DBSCAN, KMeans, etc.).

CuML

Did they implement the clustering algorithm themselves? cuML is a GPU-accelerated scikit-learn-like package that covers many of the common ML algorithms.

https://github.com/rapidsai/cuml

> cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU equivalents. For details on performance, see the cuML Benchmarks Notebook.

Cython code

Take a look at RAPIDS CUML https://github.com/rapidsai/cuml. It's useful for most common ML algorithms. Feel free to create Github issues for feature requests & bugs.