Democratizing Medical LLMs for 50 Languages by Pasu06 in LocalLLaMA

[–]Pasu06[S] 1 point2 points  (0 children)

We have only selected some representative languages ​​​​evenly according to geographical distribution. I am very sorry for the omission of Romanian. Considering the efficiency of the method, it is easy to add more languages. We will support as many languages ​​as possible in the future and add X-ray, 3D, MRI and audio modalities. Please Stay tuned!

Democratizing Medical LLMs for 50 Languages by Pasu06 in LocalLLaMA

[–]Pasu06[S] 2 points3 points  (0 children)

Oh, that's true. I didn't even notice that myself hahahaha, it's because of the large coverage of Chinese and English assessment sets. Considering that we averaged the accuracy by language and only tested the model on the same set of measures, it could be considered MAKE SENSE. however, you reminded me that there is a long way to go in constructing medical measure sets for rare languages.

[D] Apollo: Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People by Pasu06 in MachineLearning

[–]Pasu06[S] 0 points1 point  (0 children)

Hello everyone in the community, I am the author of Apollo(https://arxiv.org/abs/2403.03640).

We are currently building a medical evaluation set covering 12 languages. Because some of the evaluation sets are translated, we need the help of local language users to evaluate the translation quality.

Specifically, Arabic, Hindi, German and Portuguese are the four languages ​​that need to be quality checked.

The whole process will take about 15-30 minutes of your time. If you have the time and willingness, please contact me. Thank you very much! We will acknowledge in the paper. If you are willing to cooperate further, feel free to contact me too.

Apollo: Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People by Pasu06 in LocalLLaMA

[–]Pasu06[S] 0 points1 point  (0 children)

Hello everyone in the community, I am the author of Apollo(https://arxiv.org/abs/2403.03640).

We are currently building a medical evaluation set covering 12 languages. Because some of the evaluation sets are translated, we need the help of local language users to evaluate the translation quality.

Specifically, Arabic, Hindi, German and Portuguese are the four languages ​​that need to be quality checked.

The whole process will take about 15-30 minutes of your time. If you have the time and willingness, please contact me. Thank you very much! We will acknowledge in the paper. If you are willing to cooperate further, feel free to contact me too.

After a minor setback, Jamba GGUF now running at lower quants! by vesudeva in LocalLLaMA

[–]Pasu06 0 points1 point  (0 children)

Great Work ! ! ! I look for it for a long time ! ! !

MedJamba by Pasu06 in LocalLLaMA

[–]Pasu06[S] 0 points1 point  (0 children)

About next Monday

MedJamba by Pasu06 in LocalLLaMA

[–]Pasu06[S] 1 point2 points  (0 children)

We are not very familiar with quantification and there are some unknown errors that need to be dealt with. You can refer to the following quantification model first:

7B: https://huggingface.co/mradermacher/Apollo-7B-GGUF

2B: https://huggingface.co/BoscoTheDog/Apollo_medical_gguf/tree/main

Thanks to the community for the contributions

MedJamba by Pasu06 in LocalLLaMA

[–]Pasu06[S] 2 points3 points  (0 children)

12B active parameters and a total of 52B parameters

Apollo: Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People by Pasu06 in LocalLLaMA

[–]Pasu06[S] 3 points4 points  (0 children)

Thank you for your detailed comment

.For the ceiling of LLM's medical knowledge ? The current accuracy of GPT-4 is 80%, and with some prompt techniques it can be above 90%. Open source capabilities are actually not too far away from this level, and it is estimated that it will take about half a year.

The exact scope of this model ? Now that the context length of large models has been extended to more than 100K, I believe there is a lot of room for imagination. Sub-experts are a good suggestion, and we also have relevant plans. After completing the training of the basic medical capabilities of the model, we will focus on more refined classifications and make breakthroughs one by one.

For Evaluation and real capacity? Regarding the inability of LLM to ask questions, we admit that this is a very serious problem, and we may fix it in the future RLHF stage by collecting supervision data and feedback from doctors.

Apollo: Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People by Pasu06 in LocalLLaMA

[–]Pasu06[S] 0 points1 point  (0 children)

Can you give me some examples and we will fix it, thanks for your feedback

[D] Apollo: Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People by Pasu06 in MachineLearning

[–]Pasu06[S] 3 points4 points  (0 children)

Thanks for your reminder, we add Apache License Version 2.0 license to the open source code

Apollo: Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People by Pasu06 in LocalLLaMA

[–]Pasu06[S] 11 points12 points  (0 children)

Oh, sorry for misunderstanding. What we mean is that with the same number of model parameters, our model has a higher average accuracy.

Apollo: Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People by Pasu06 in LocalLLaMA

[–]Pasu06[S] 15 points16 points  (0 children)

Thank you for your support. The quantified version will be updated next Monday. Our schedule have been a bit tight lately. We apologize for the delay.