Ali El Filali's picture

Ali El Filali

alielfilali01

AI & ML interests

AI Psychometrician ? | NLP (mainly for Arabic) | Interests include Reinforcement Learning and Cognitive sciences among others

Recent Activity

updated a dataset 2 days ago
inceptionai/requests-dataset
updated a dataset 2 days ago
inceptionai/requests-dataset
updated a dataset 2 days ago
inceptionai/requests-dataset
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Gradio-Themes-Party's profile picture Arabic Machine Learning 's profile picture BigLAM: BigScience Libraries, Archives and Museums's profile picture Stable Diffusion Dreambooth Concepts Library's profile picture Blog-explorers's profile picture ASAS AI's profile picture Nt3awnou's profile picture Qwen's profile picture Mixed Arabic Datasets's profile picture ZeroGPU Explorers's profile picture 2A2I Legacy Models & Datasets's profile picture AtlasIA's profile picture 2A2I's profile picture Open Arabic LLM Leaderboard's profile picture MLX Community's profile picture Social Post Explorers's profile picture C4AI Community's profile picture Dev Mode Explorers's profile picture Chinese LLMs on Hugging Face's profile picture ThinkAI's profile picture KABOUR's profile picture Hugging Face Discord Community's profile picture llmc's profile picture Arabic Translation Prompt Engineering's profile picture Inception's profile picture Dataset Tools's profile picture ml-fw-prerelease's profile picture Data Is Better Together Contributor's profile picture Donut Earthers ๐Ÿฉ's profile picture QudraTech's profile picture 3C3H's profile picture Conception's profile picture Inception & MBZUAI VLM Eval Team's profile picture

alielfilali01's activity

reacted to clem's post with ๐Ÿค— 4 days ago
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4237
We just crossed 1,500,000 public models on Hugging Face (and 500k spaces, 330k datasets, 50k papers). One new repository is created every 15 seconds. Congratulations all!
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reacted to BrigitteTousi's post with ๐Ÿš€ 4 days ago
reacted to MohamedRashad's post with ๐Ÿš€โค๏ธ 24 days ago
posted an update 25 days ago
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๐Ÿšจ Arabic LLM Evaluation ๐Ÿšจ

Few models join the ranking of 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.
reacted to merve's post with ๐Ÿš€๐Ÿง  25 days ago
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Google just released PaliGemma 2 Mix: new versatile instruction vision language models ๐Ÿ”ฅ

> Three new models: 3B, 10B, 28B with res 224, 448 ๐Ÿ’™
> Can do vision language tasks with open-ended prompts, understand documents, and segment or detect anything ๐Ÿคฏ

Read more https://huggingface.co/blog/paligemma2mix
Try the demo google/paligemma2-10b-mix
All models are here google/paligemma-2-mix-67ac6a251aaf3ee73679dcc4
reacted to dreamerdeo's post with ๐Ÿค—๐Ÿš€ 25 days ago
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๐Ÿš€ Excited to share our technical report on the Southeast Asian multilingual model Sailor2 and its latest updates!

Our 49-page report details Sailor2's development journey, including multilingual data cleaning, small model data mixture simulations, multi-stage continual pre-training, multi-stage post-training, and multi-cultural multi-lingual evaluations. Sailor2 aims to streamline the multilingual model pre-training process efficiently for the community.

๐Ÿงญ We highlight Sailor2's impressive performance in low-resource language translation scenarios and its cultural understanding advantages in Southeast Asia, promoting practical applications for regional languages.

Model updates include:ย 
๐Ÿ’ก More precise outputs: Reduced redundancy in model outputs through refined post-training data and optimization techniques.ย 
๐ŸŒˆ Handling longer texts: Expanded to handle up to 128K context length in Southeast Asian languages through long-text training.ย 
โšก๏ธ Faster inference: Achieved 2.5x faster inference speed with speculative decoding.ย 
๐ŸŒช๏ธ More model sizes: Introduced new sizes of 3B and 14B through model pruning.

๐ŸŒŸ All models are Apache-licensed for commercial use; development tools (code, resources) are open-source.

๐Ÿ“š Technical report: Sailor2: Sailing in South-East Asia with Inclusive Multilingual LLMs (2502.12982)ย 
๐Ÿค–๏ธ Models: sail/sailor2-language-models-674d7c9e6b4dbbd9a869906bย 
๐Ÿ’ฌ Demo: sail/Sailor2-20B-Chatย 
๐Ÿ“ฃ Sailor2 community: https://huggingface.co/sailor2
reacted to fantos's post with ๐Ÿ”ฅ about 2 months ago
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๐Ÿš€ HuggingFace Spaces Ranking Tracker - Your Complete AI Trend Analytics!

Introducing the Spaces Ranking Tracker, a comprehensive analytics dashboard that tracks and analyzes every AI application in the HuggingFace ecosystem.

โœจ Key Features:
โ€ข Real-time tracking of daily ranking changes over 30 days
โ€ข Detailed analysis of top 100 trending spaces
โ€ข User-based integrated score visualization
โ€ข One-click access to space details
โ€ข Interactive rank change graphs

๐Ÿ“Š Dashboard Components:
1. Main Dashboard
- Daily rank trend graphs
- Top 20 creators' combined score chart
- Detailed space information cards
- Real-time trending score updates

2. Space Detailed Analysis
- Creation date, current rank, and trending score
- 30-day ranking history
- Direct space access
- Custom color coding for intuitive rank display

๐ŸŽฏ How to Use:
โ€ข Monitor latest AI community trends
โ€ข Track your project's performance
โ€ข Discover popular AI demos
โ€ข Analyze competing projects
โ€ข Follow AI ecosystem dynamics

3. Interactive Features
- Custom filtering options
- Sorting by various metrics
- Detailed performance statistics
- Comprehensive trending scores
- Historical data tracking

Stay on top of every movement in the HuggingFace ecosystem with daily ranking updates! ๐Ÿ‘‰ Try it now!

๐Ÿ”— Access Dashboard: fantos/Ranking-Tracker
#HuggingFace #AI #DataVisualization #TrendAnalysis #AITrends
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reacted to burtenshaw's post with ๐Ÿš€ about 2 months ago
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Manic few days in open source AI, with game changing development all over the place. Here's a round up of the resources:

- The science team at @huggingface reproduced and open source the seek r1. https://github.com/huggingface/open-r1
- @qwen released a series of models with 1 million token context! https://qwenlm.github.io/blog/qwen2.5-1m/
- SmolVLM got even smaller with completely new variants at 256m and 500m https://huggingface.co/blog/smolervlm

There's so much you could do with these developments. Especially combining them together into agentic applications or fine-tuning them on your use case.
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reacted to AdinaY's post with ๐Ÿ”ฅ๐Ÿง  about 2 months ago
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2852
BIG release by DeepSeek AI๐Ÿ”ฅ๐Ÿ”ฅ๐Ÿ”ฅ

DeepSeek-R1 & DeepSeek-R1-Zero: two 660B reasoning models are here, alongside 6 distilled dense models (based on Llama & Qwen) for the community!
https://huggingface.co/deepseek-ai
deepseek-ai/DeepSeek-R1

โœจ MIT License : enabling distillation for custom models
โœจ 32B & 70B models match OpenAI o1-mini in multiple capabilities
โœจ API live now! Access Chain of Thought reasoning with model='deepseek-reasoner'
reacted to MohamedRashad's post with โค๏ธ 2 months ago
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2078
The winners of Best Paper Award in NeurIPs2024 (FoundationVision) Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction (2404.02905) has just released a new paper called infinty:
Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis (2412.04431)

And i managed to build a space for it so anyone can try it out: MohamedRashad/Infinity

The idea of a text to image model using autoregressive archticture is quite interesting in my opinion.
posted an update 2 months ago
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3C3H AraGen Leaderboard welcomes today deepseek-ai/DeepSeek-V3 and 12 other models (including the late gpt-3.5 ๐Ÿ’€) 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: inceptionai/AraGen-Leaderboard
reacted to prithivMLmods's post with ๐Ÿš€ 2 months ago
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Reasoning SmolLM2 ๐Ÿš€

๐ŸŽฏFine-tuning SmolLM2 on a lightweight synthetic reasoning dataset for reasoning-specific tasks. Future updates will focus on lightweight, blazing-fast reasoning models. Until then, check out the blog for fine-tuning details.

๐Ÿ”ฅBlog : https://huggingface.co/blog/prithivMLmods/smollm2-ft

๐Ÿ”ผ Models :
+ SmolLM2-CoT-360M : prithivMLmods/SmolLM2-CoT-360M
+ Reasoning-SmolLM2-135M : prithivMLmods/Reasoning-SmolLM2-135M
+ SmolLM2-CoT-360M-GGUF : prithivMLmods/SmolLM2-CoT-360M-GGUF

๐Ÿค  Other Details :
+ Demo : prithivMLmods/SmolLM2-CoT-360M
+ Fine-tune nB : prithivMLmods/SmolLM2-CoT-360M




reacted to merve's post with โค๏ธ 2 months ago
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4891
supercharge your LLM apps with smolagents ๐Ÿ”ฅ

however cool your LLM is, without being agentic it can only go so far

enter smolagents: a new agent library by Hugging Face to make the LLM write code, do analysis and automate boring stuff!

Here's our blog for you to get started https://huggingface.co/blog/smolagents
reacted to suayptalha's post with โค๏ธ 3 months ago
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๐Ÿš€ Introducing ๐…๐ข๐ซ๐ฌ๐ญ ๐‡๐ฎ๐ ๐ ๐ข๐ง๐  ๐…๐š๐œ๐ž ๐ˆ๐ง๐ญ๐ž๐ ๐ซ๐š๐ญ๐ข๐จ๐ง ๐จ๐Ÿ ๐ฆ๐ข๐ง๐†๐‘๐” ๐Œ๐จ๐๐ž๐ฅ๐ฌ from the paper ๐–๐ž๐ซ๐ž ๐‘๐๐๐ฌ ๐€๐ฅ๐ฅ ๐–๐ž ๐๐ž๐ž๐๐ž๐?

๐Ÿ–ฅ I have integrated ๐ง๐ž๐ฑ๐ญ-๐ ๐ž๐ง๐ž๐ซ๐š๐ญ๐ข๐จ๐ง ๐‘๐๐๐ฌ, specifically minGRU, which offer faster performance compared to Transformer architectures, into HuggingFace. This allows users to leverage the lighter and more efficient minGRU models with the "๐ญ๐ซ๐š๐ง๐ฌ๐Ÿ๐จ๐ซ๐ฆ๐ž๐ซ๐ฌ" ๐ฅ๐ข๐›๐ซ๐š๐ซ๐ฒ for both usage and training.

๐Ÿ’ป I integrated two main tasks: ๐Œ๐ข๐ง๐†๐‘๐”๐…๐จ๐ซ๐’๐ž๐ช๐ฎ๐ž๐ง๐œ๐ž๐‚๐ฅ๐š๐ฌ๐ฌ๐ข๐Ÿ๐ข๐œ๐š๐ญ๐ข๐จ๐ง and ๐Œ๐ข๐ง๐†๐‘๐”๐…๐จ๐ซ๐‚๐š๐ฎ๐ฌ๐š๐ฅ๐‹๐Œ.

๐Œ๐ข๐ง๐†๐‘๐”๐…๐จ๐ซ๐’๐ž๐ช๐ฎ๐ž๐ง๐œ๐ž๐‚๐ฅ๐š๐ฌ๐ฌ๐ข๐Ÿ๐ข๐œ๐š๐ญ๐ข๐จ๐ง:
You can use this class for ๐’๐ž๐ช๐ฎ๐ž๐ง๐œ๐ž ๐‚๐ฅ๐š๐ฌ๐ฌ๐ข๐Ÿ๐ข๐œ๐š๐ญ๐ข๐จ๐ง tasks. I also trained a Sentiment Analysis model with stanfordnlp/imdb dataset.

๐Œ๐ข๐ง๐†๐‘๐”๐…๐จ๐ซ๐‚๐š๐ฎ๐ฌ๐š๐ฅ๐‹๐Œ:
You can use this class for ๐‚๐š๐ฎ๐ฌ๐š๐ฅ ๐‹๐š๐ง๐ ๐ฎ๐š๐ ๐ž ๐Œ๐จ๐๐ž๐ฅ tasks such as GPT, Llama. I also trained an example model with roneneldan/TinyStories dataset. You can fine-tune and use it!

๐Ÿ”— ๐‹๐ข๐ง๐ค๐ฌ:
Models: suayptalha/mingru-676fe8d90760d01b7955d7ab
GitHub: https://github.com/suayptalha/minGRU-hf
LinkedIn Post: https://www.linkedin.com/posts/suayp-talha-kocabay_mingru-a-suayptalha-collection-activity-7278755484172439552-wNY1

๐Ÿ“ฐ ๐‚๐ซ๐ž๐๐ข๐ญ๐ฌ:
Paper Link: https://arxiv.org/abs/2410.01201

I am thankful to Leo Feng, Frederick Tung, Mohamed Osama Ahmed, Yoshua Bengio and Hossein Hajimirsadeghi for their papers.
posted an update 3 months ago
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~75% on the challenging GPQA with only 40M parameters ๐Ÿ”ฅ๐Ÿฅณ

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, itโ€™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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