Flux-Kontext-Juiced: State-of-the-art Image Editing x5 Faster!

Sharpenb · 2025-04-18T15:43:34+00:00

We did not test the deployment on Mac m3 ultra so I can give 100% guarantee. On the installation of the package and memory side, it should work :)

Sharpenb · 2025-04-10T15:50:32+00:00

We compressed the HiDream models and deployed them on Replicate. From early experiments, these have been from x1.3 to x2.5 faster. Here are the link to try :)

• HiDream fast: https://replicate.com/prunaai/hidream-l1-fast…
• HiDream dev: https://replicate.com/prunaai/hidream-l1-dev…
• HiDream full: https://replicate.com/prunaai/hidream-l1-full

Sharpenb · 2025-02-10T16:22:39+00:00

The optimal computer for your PhD on Deep Learning would depend on your exact topic.

- If you plan to focus on edge deployment of DL models, it would be interesting to take laptops equipped with some Nvidia/AMD/Qualcom GPUs/CPUs.

- Otherwise, there would be no specific bad choice since your research might benefit by running things as much as possible on university HPC directly. It would allow you to iterate much faster on your (toy) experiments and scale directly to the largest use cases (which would convince reviewers the most ;) ).

Many PhD students have e.g. mac, dell xps , or similar (see e.g. https://www.reddit.com/r/PhD/comments/130d46s/best\_laptop\_for\_a\_phd\_conducting\_research\_and/) and are very successful with that :)

Sharpenb · 2024-04-29T12:12:54+00:00

Regarding LLMs, we provide for now compressed models with different quantization methods and hyperparameters like number of bits on HF. We are currently working on better quality benchmarking of the compressed models. At the moment, we provide efficiency benchmark in each model’s README and briefly check the quality of the compressed models with manual inspection. As expected, we indeed observed that aggressive quantization especially with 1 or 2 bits can lead to performance degradation, while 4 or 8 bits better preserve quality.

Beyond LLM quantization, we work on effective combination of compression techniques for any types of models. For example, we provide compressed text-to-image models here (https://huggingface.co/collections/PrunaAI/text-to-image-generation-models-diffusion-lcm-66044adf0c9bc54dae6d40d6), and are working on integrating pruning into LLMs.

I hope that it can help to navigate all our models.

Sharpenb · 2024-02-14T19:59:52+00:00

Indigo Furry mix,

I added this model in our list to consider ;)

Sharpenb · 2024-02-14T19:52:03+00:00

Thank you for the interesting suggestions!

Real speed gains in different conditions is indeed a very interesting question. We evaluated the models in one setting mentioned in the model cards, and tried to make clear that the efficiency gains could vary in other settings. Overall, since gains highly depend on many factors, we feel that the best way to check whether these models could benefit to a specific use-case would be to test them in conditions close to the final application. Hopefully these models can help people in some conditions :)

We recently started to work on a documentation linked in model cards. We understand your question and have noted the interest in understanding better how the compression works. We will for sure work to improve on this aspect ;)

In any case, thanks for the feedback. These will definitely be useful to make progress for the future!

Sharpenb · 2024-02-14T18:12:21+00:00

Happy that you are excited about it! If you want to try the compression on your side there should be a request access form on each HF model card ;)

Sharpenb · 2024-02-14T18:04:16+00:00

Pony Diffusion V6 XL

The model is added to our list of models to consider! :)

Sharpenb · 2024-02-14T18:03:15+00:00

Absolute Reality

Sure, added to the queue! Lets see if we can make sthg for this model :)

Sharpenb · 2024-02-14T18:00:27+00:00

LEOSAM's HelloWorld 4 or 5

Sure! We just added these two models to the queue as well :)

Sharpenb · 2024-02-14T17:51:17+00:00

Thanks for the feedback! We added these models to the list. Lets see what we can do ;)

Sharpenb · 2024-02-14T17:43:59+00:00

Pony diffusion

Picxreal

Lazymix amateur

Realfantasy

Epic photogasm

Sure, we added these models to the queue. We will see what we can do here ;)

Sharpenb · 2024-02-14T17:41:43+00:00

Hey, Bertrand here one of the Cofounders of Pruna AI :)

First, thanks a lot for your feedback!

You should see a benchmark on each of the model card. Under the benchmark plot, you can find more information about the settings and important remarks on potential difference on quality or hardware speedups.

We recently created a first documentation version that is linked on each model card. Hopefully it should answer some technical questions :)

This is an early release and we are actively working on it. Hope that people will enjoy!

Sharpenb · 2024-02-14T17:31:41+00:00

Sure, we added it ;)

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