๐ FineMath
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FineMath datasets and ablation models
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EDDY GIUSEPE CHIRINOS ISIDRO, PhD
EddyGiusepe
AI & ML interests
Speech Processing (ASR, Speaker Identification, Text-to-Speech)
NLP (text classification, Sentence similarity, Token classification, etc)
Computer vision (Image classification)
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davanstrien's
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2472
First dataset for the new Hugging Face Bluesky community organisation:
bluesky-community/one-million-bluesky-posts ๐ฆ
๐ 1M public posts from Bluesky's firehose API
๐ Includes text, metadata, and language predictions
๐ฌ Perfect to experiment with using ML for Bluesky ๐ค
Excited to see people build more open tools for a more open social media platform!
๐ 1M public posts from Bluesky's firehose API
๐ Includes text, metadata, and language predictions
๐ฌ Perfect to experiment with using ML for Bluesky ๐ค
Excited to see people build more open tools for a more open social media platform!
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489
Increasingly, LLMs are becoming very useful for helping scale annotation tasks, i.e. labelling and filtering. When combined with the structured generation, this can be a very scalable way of doing some pre-annotation without requiring a large team of human annotators.
However, there are quite a few cases where it still doesn't work well. This is a nice paper looking at the limitations of LLM as an annotator for Low Resource Languages: On Limitations of LLM as Annotator for Low Resource Languages (2411.17637).
Humans will still have an important role in the loop to help improve models for all languages (and domains).
However, there are quite a few cases where it still doesn't work well. This is a nice paper looking at the limitations of LLM as an annotator for Low Resource Languages: On Limitations of LLM as Annotator for Low Resource Languages (2411.17637).
Humans will still have an important role in the loop to help improve models for all languages (and domains).
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dvilasuero's
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2261
๐ Announcing Global-MMLU: an improved MMLU Open dataset with evaluation coverage across 42 languages, built with Argilla and the Hugging Face community.
Global-MMLU is the result of months of work with the goal of advancing Multilingual LLM evaluation. It's been an amazing open science effort with collaborators from Cohere For AI, Mila - Quebec Artificial Intelligence Institute, EPFL, Massachusetts Institute of Technology, AI Singapore, National University of Singapore, KAIST, Instituto Superior Tรฉcnico, Carnegie Mellon University, CONICET, and University of Buenos Aires.
๐ท๏ธ +200 contributors used Argilla MMLU questions where regional, dialect, or cultural knowledge was required to answer correctly. 85% of the questions required Western-centric knowledge!
Thanks to this annotation process, the open dataset contains two subsets:
1. ๐ฝ Culturally Agnostic: no specific regional, cultural knowledge is required.
2. โ๏ธ Culturally Sensitive: requires dialect, cultural knowledge or geographic knowledge to answer correctly.
Moreover, we provide high quality translations of 25 out of 42 languages, thanks again to the community and professional annotators leveraging Argilla on the Hub.
I hope this will ensure a better understanding of the limitations and challenges for making open AI useful for many languages.
Dataset: CohereForAI/Global-MMLU
Global-MMLU is the result of months of work with the goal of advancing Multilingual LLM evaluation. It's been an amazing open science effort with collaborators from Cohere For AI, Mila - Quebec Artificial Intelligence Institute, EPFL, Massachusetts Institute of Technology, AI Singapore, National University of Singapore, KAIST, Instituto Superior Tรฉcnico, Carnegie Mellon University, CONICET, and University of Buenos Aires.
๐ท๏ธ +200 contributors used Argilla MMLU questions where regional, dialect, or cultural knowledge was required to answer correctly. 85% of the questions required Western-centric knowledge!
Thanks to this annotation process, the open dataset contains two subsets:
1. ๐ฝ Culturally Agnostic: no specific regional, cultural knowledge is required.
2. โ๏ธ Culturally Sensitive: requires dialect, cultural knowledge or geographic knowledge to answer correctly.
Moreover, we provide high quality translations of 25 out of 42 languages, thanks again to the community and professional annotators leveraging Argilla on the Hub.
I hope this will ensure a better understanding of the limitations and challenges for making open AI useful for many languages.
Dataset: CohereForAI/Global-MMLU
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1556
๐ FastLlama Series is Live!
๐ฆพ Experience faster, lighter, and smarter language models! The new FastLlama makes Meta's LLaMA models work with smaller file sizes, lower system requirements, and higher performance. The model supports 8 languages, including English, German, and Spanish.
๐ค Built on the LLaMA 3.2-1B-Instruct model, fine-tuned with Hugging Face's SmolTalk and MetaMathQA-50k datasets, and powered by LoRA (Low-Rank Adaptation) for groundbreaking mathematical reasoning.
๐ป Its compact size makes it versatile for a wide range of applications!
๐ฌ Chat with the model:
๐ Chat Link: suayptalha/Chat-with-FastLlama
๐ Model Link: suayptalha/FastLlama-3.2-1B-Instruct
๐ฆพ Experience faster, lighter, and smarter language models! The new FastLlama makes Meta's LLaMA models work with smaller file sizes, lower system requirements, and higher performance. The model supports 8 languages, including English, German, and Spanish.
๐ค Built on the LLaMA 3.2-1B-Instruct model, fine-tuned with Hugging Face's SmolTalk and MetaMathQA-50k datasets, and powered by LoRA (Low-Rank Adaptation) for groundbreaking mathematical reasoning.
๐ป Its compact size makes it versatile for a wide range of applications!
๐ฌ Chat with the model:
๐ Chat Link: suayptalha/Chat-with-FastLlama
๐ Model Link: suayptalha/FastLlama-3.2-1B-Instruct
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4144
๐ Digital Odyssey: AI Image & Video Generation Platform ๐จ
Welcome to our all-in-one AI platform for image and video generation! ๐
โจ Key Features
๐จ High-quality image generation from text
๐ฅ Video creation from still images
๐ Multi-language support with automatic translation
๐ ๏ธ Advanced customization options
๐ซ Unique Advantages
โก Fast and accurate results using FLUX.1-dev and Hyper-SD models
๐ Robust content safety filtering system
๐ฏ Intuitive user interface
๐ ๏ธ Extended toolkit including image upscaling and logo generation
๐ฎ How to Use
Enter your image or video description
Adjust settings as needed
Click generate
Save and share your results automatically
๐ง Tech Stack
FluxPipeline
Gradio
PyTorch
OpenCV
link: ginigen/Dokdo
Turn your imagination into reality with AI! โจ
#AI #ImageGeneration #VideoGeneration #MachineLearning #CreativeTech
Welcome to our all-in-one AI platform for image and video generation! ๐
โจ Key Features
๐จ High-quality image generation from text
๐ฅ Video creation from still images
๐ Multi-language support with automatic translation
๐ ๏ธ Advanced customization options
๐ซ Unique Advantages
โก Fast and accurate results using FLUX.1-dev and Hyper-SD models
๐ Robust content safety filtering system
๐ฏ Intuitive user interface
๐ ๏ธ Extended toolkit including image upscaling and logo generation
๐ฎ How to Use
Enter your image or video description
Adjust settings as needed
Click generate
Save and share your results automatically
๐ง Tech Stack
FluxPipeline
Gradio
PyTorch
OpenCV
link: ginigen/Dokdo
Turn your imagination into reality with AI! โจ
#AI #ImageGeneration #VideoGeneration #MachineLearning #CreativeTech
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