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takarajordan 
posted an update 3 days ago
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1462
AI research over coffee ☕️
No abstracts, just bullet points.
Start your day here: https://tldr.takara.ai
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takarajordan 
posted an update 12 days ago
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1848
Takara takes 3rd place in the {tech:munich} AI hackathon with Fudeno!

A little over 2 weeks ago @aldigobbler and I set out to create the largest MultiModal SVG dataset ever created, we succeeded in this and when I was in Munich, Germany I took it one step further and made an entire app with it!

We fine-tuned Mistral Small, made a Next.JS application and blew some minds, taking 3rd place out of over 100 hackers. So cool!

If you want to see the dataset, please see below.

takara-ai/fudeno-instruct-4M
not-lain 
posted an update 25 days ago
alielfilali01 
posted an update about 2 months ago
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907
🚨 Arabic LLM Evaluation 🚨

Few models join the ranking of https://huggingface.co/spaces/inceptionai/AraGen-Leaderboard Today.

The new MistralAI model, Saba, is quite impressive, Top10 ! Well done @arthurmensch and team.

Sadly Mistral did not follow its strategy about public weights this time, we hope this changes soon and we get the model with a permissive license.

We added other Mistral models and apparently, we have been sleeping on mistralai/Mistral-Large-Instruct-2411 !

Another impressive model that joined the ranking today is ALLaM-AI/ALLaM-7B-Instruct-preview. After a long wait finally ALLaM is here and it is IMPRESSIVE given its size !

ALLaM is ranked on OALL/Open-Arabic-LLM-Leaderboard as well.
not-lain 
posted an update 2 months ago
not-lain 
posted an update 3 months ago
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1685
we now have more than 2000 public AI models using ModelHubMixin🤗
not-lain 
posted an update 3 months ago
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4048
Published a new blogpost 📖
In this blogpost I have gone through the transformers' architecture emphasizing how shapes propagate throughout each layer.
🔗 https://huggingface.co/blog/not-lain/tensor-dims
some interesting takeaways :
alielfilali01 
posted an update 3 months ago
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2069
3C3H AraGen Leaderboard welcomes today deepseek-ai/DeepSeek-V3 and 12 other models (including the late gpt-3.5 💀) to the ranking of best LLMs in Arabic !


Observations:
- DeepSeek-v3 ranked 3rd and only Open model among the top 5 !

- A 14B open model ( Qwen/Qwen2.5-14B-Instruct) outperforms gpt-3.5-turbo-0125 (from last year). This shows how much we came in advancing and supporting Arabic presence within the LLM ecosystem !

- Contrary to what observed in likelihood-acc leaderboards (like OALL/Open-Arabic-LLM-Leaderboard) further finetuned models like maldv/Qwentile2.5-32B-Instruct actually decreased the performance compared to the original model Qwen/Qwen2.5-32B-Instruct.
It's worth to note that the decrease is statiscally insignificant which imply that at best, the out-domain finetuning do not really hurts the model original capabilities acquired during pretraining.
Previous work addressed this (finetuning VS pretraining) but more investigation in this regard is required (any PhDs here ? This could be your question ...)


Check out the latest rankings: https://huggingface.co/spaces/inceptionai/AraGen-Leaderboard
alielfilali01 
posted an update 3 months ago
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1999
~75% on the challenging GPQA with only 40M parameters 🔥🥳

GREAT ACHIEVEMENT ! Or is it ?

This new Work, "Data Laundering: Artificially Boosting Benchmark Results through Knowledge Distillation", take out the mystery about many models i personally suspected their results. Speacially on leaderboards other than the english one, Like the Open Arabic LLM Leaderbaord OALL/Open-Arabic-LLM-Leaderboard.

The authors of this work, first started by training a model on the GPQA data, which, unsurprisingly, led to the model achieving 100% performance.

Afterward, they trained what they referred to as a 'legitimate' model on legitimate data (MedMCQA). However, they introduced a distillation loss from the earlier, 'cheated' model.

What they discovered was fascinating: the knowledge of GPQA leaked through this distillation loss, even though the legitimate model was never explicitly trained on GPQA during this stage.

This raises important questions about the careful use of distillation in model training, especially when the training data is opaque. As they demonstrated, it’s apparently possible to (intentionally or unintentionally) leak test data through this method.

Find out more: Data Laundering: Artificially Boosting Benchmark Results through Knowledge Distillation (2412.15255)
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takarajordan 
posted an update 4 months ago
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I made an RSS feed for HuggingFace Daily Papers!! 🤗

Just Subscribe here: https://papers.takara.ai/api/feed

It updates every 24 hours, completely written as a serverless go script with a Redis cache (to avoid hitting HF all the time).

I'm open sourcing the code, you can check out my repo and deploy it on Vercel extremely easily!
https://github.com/404missinglink/HF-Daily-Papers-Feeds

thanks to @John6666 @p3nGu1nZz for your early support
alielfilali01 
posted an update 4 months ago
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3494
Unpopular opinion: Open Source takes courage to do !

Not everyone is brave enough to release what they have done (the way they've done it) to the wild to be judged !
It really requires a high level of "knowing wth are you doing" ! It's kind of a super power !

Cheers to the heroes here who see this!
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takarajordan 
posted an update 4 months ago
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2479
I'm super excited to release my first open-source text dataset:

WorldScenario 20K is a novel dataset of 20,000 synthetically generated multi-stakeholder scenarios designed to simulate real-world decision-making processes. Each scenario explores a unique environmental, societal, or economic issue.

I used the brand new meta-llama/Llama-3.3-70B-Instruct model to generate this dataset and I put the dataset through some post processing to clean and evaluate the dataset for diversity.

I'd appreciate some feedback and thoughts on my new release! Thanks!

takarajordan/WorldScenario_20K
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alielfilali01 
posted an update 4 months ago
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Apparently i forgot to put this here !

Well, this is a bit late but consider given our recent blog a read if you are interested in Evaluation.

You don't have to be into Arabic NLP in order to read it, the main contribution we are introducing is a new evaluation measure for NLG. We made the fisrt application of this measure on Arabic for now and we will be working with colleagues from the community to expand it to other languages.

Blog:
Rethinking LLM Evaluation with 3C3H: AraGen Benchmark and Leaderboard
https://huggingface.co/blog/leaderboard-3c3h-aragen

Space:
https://huggingface.co/spaces/inceptionai/AraGen-Leaderboard

Give it a read and let me know your thoughts 🤗
p3nGu1nZz 
in donut-earth/donut-AE 4 months ago

enhance-setup-script

4
#1 opened 4 months ago by
p3nGu1nZz
aldigobbler 
in donut-earth/donut-AE 4 months ago

enhance-setup-script

4
#1 opened 4 months ago by
p3nGu1nZz
p3nGu1nZz 
updated a model 4 months ago
aldigobbler 
updated a Space 4 months ago
aldigobbler 
updated a model 4 months ago
takarajordan 
posted an update 4 months ago
aldigobbler 
posted an update 4 months ago