Bridging the Data Provenance Gap Across Text, Speech and Video
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ljvmiranda921
authored
2
papers
about 14 hours ago
prithivMLmods
posted
an
update
about 16 hours ago
Post
1581
Reasoning SmolLM2 🚀
🎯Fine-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.
🔥Blog : https://huggingface.co/blog/prithivMLmods/smollm2-ft
🔼 Models :
+ SmolLM2-CoT-360M : prithivMLmods/SmolLM2-CoT-360M
+ Reasoning-SmolLM2-135M : prithivMLmods/Reasoning-SmolLM2-135M
+ SmolLM2-CoT-360M-GGUF : prithivMLmods/SmolLM2-CoT-360M-GGUF
🤠 Other Details :
+ Demo : prithivMLmods/SmolLM2-CoT-360M
+ Fine-tune nB : prithivMLmods/SmolLM2-CoT-360M
🎯Fine-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.
🔥Blog : https://huggingface.co/blog/prithivMLmods/smollm2-ft
🔼 Models :
+ SmolLM2-CoT-360M : prithivMLmods/SmolLM2-CoT-360M
+ Reasoning-SmolLM2-135M : prithivMLmods/Reasoning-SmolLM2-135M
+ SmolLM2-CoT-360M-GGUF : prithivMLmods/SmolLM2-CoT-360M-GGUF
🤠 Other Details :
+ Demo : prithivMLmods/SmolLM2-CoT-360M
+ Fine-tune nB : prithivMLmods/SmolLM2-CoT-360M
Sri-Vigneshwar-DJ
posted
an
update
2 days ago
Post
2100
Combining smolagents with Anthropic’s best practices simplifies building powerful AI agents:
1. Code-Based Agents: Write actions as Python code, reducing steps by 30%.
2. Prompt Chaining: Break tasks into sequential subtasks with validation gates.
3. Routing: Classify inputs and direct them to specialized handlers.
4. Fallback: Handle tasks even if classification fails.
https://huggingface.co/blog/Sri-Vigneshwar-DJ/building-effective-agents-with-anthropics-best-pra
1. Code-Based Agents: Write actions as Python code, reducing steps by 30%.
2. Prompt Chaining: Break tasks into sequential subtasks with validation gates.
3. Routing: Classify inputs and direct them to specialized handlers.
4. Fallback: Handle tasks even if classification fails.
https://huggingface.co/blog/Sri-Vigneshwar-DJ/building-effective-agents-with-anthropics-best-pra
davidberenstein1957
posted
an
update
3 days ago
Post
1750
Fine-tune a SmolLM on domain-specific synthetic data from a LLM
Blog: https://huggingface.co/blog/davidberenstein1957/fine-tune-a-smollm-on-synthetic-data-of-llm
Blog: https://huggingface.co/blog/davidberenstein1957/fine-tune-a-smollm-on-synthetic-data-of-llm
- 1 reply
prithivMLmods
posted
an
update
6 days ago
Post
3553
Triangulum Catalogued 🔥💫
🎯Triangulum is a collection of pretrained and instruction-tuned generative models, designed for multilingual applications. These models are trained using synthetic datasets based on long chains of thought, enabling them to perform complex reasoning tasks effectively.
+ Triangulum-10B : prithivMLmods/Triangulum-10B
+ Quants : prithivMLmods/Triangulum-10B-GGUF
+ Triangulum-5B : prithivMLmods/Triangulum-5B
+ Quants : prithivMLmods/Triangulum-5B-GGUF
+ Triangulum-1B : prithivMLmods/Triangulum-1B
+ Quants : prithivMLmods/Triangulum-1B-GGUF
🎯Triangulum is a collection of pretrained and instruction-tuned generative models, designed for multilingual applications. These models are trained using synthetic datasets based on long chains of thought, enabling them to perform complex reasoning tasks effectively.
+ Triangulum-10B : prithivMLmods/Triangulum-10B
+ Quants : prithivMLmods/Triangulum-10B-GGUF
+ Triangulum-5B : prithivMLmods/Triangulum-5B
+ Quants : prithivMLmods/Triangulum-5B-GGUF
+ Triangulum-1B : prithivMLmods/Triangulum-1B
+ Quants : prithivMLmods/Triangulum-1B-GGUF
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- 4 replies
Post
510
Hey everyone 🤗!
Check out this new Virtual Try Off model (based on SD1.5): 1aurent/TryOffAnyone
This model isn't as accurate as others (e.g. xiaozaa/cat-try-off-flux based on FLUX.1) but it sure is fast!
Check out this new Virtual Try Off model (based on SD1.5): 1aurent/TryOffAnyone
This model isn't as accurate as others (e.g. xiaozaa/cat-try-off-flux based on FLUX.1) but it sure is fast!
koalazf99
authored
a
paper
7 days ago
mmhamdy
authored
a
paper
7 days ago
davidberenstein1957
posted
an
update
7 days ago
Post
1904
Fine-tuning ModernBERT for text classification using synthetic data generation
From prompt to model in 3 steps.
1 dataset description
20 minutes of generating
60 minutes of fine-tuning on my Macbook Pro
Tutorial: https://nbsanity.com/static/552eb50cbd91bedb4e5b73fddca2664a/fine-tune-modernbert-classifier.html
From prompt to model in 3 steps.
1 dataset description
20 minutes of generating
60 minutes of fine-tuning on my Macbook Pro
Tutorial: https://nbsanity.com/static/552eb50cbd91bedb4e5b73fddca2664a/fine-tune-modernbert-classifier.html
alielfilali01
posted
an
update
8 days ago
Post
1727
~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)
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)
- 1 reply
davanstrien
posted
an
update
10 days ago
Post
2999
🇸🇰 Hovorte po slovensky? Help build better AI for Slovak!
We only need 90 more annotations to include Slovak in the next Hugging Face FineWeb2-C dataset ( data-is-better-together/fineweb-c) release!
Your contribution will help create better language models for 5+ million Slovak speakers.
Annotate here: data-is-better-together/fineweb-c.
Read more about why we're doing it: https://huggingface.co/blog/davanstrien/fineweb2-community
We only need 90 more annotations to include Slovak in the next Hugging Face FineWeb2-C dataset ( data-is-better-together/fineweb-c) release!
Your contribution will help create better language models for 5+ million Slovak speakers.
Annotate here: data-is-better-together/fineweb-c.
Read more about why we're doing it: https://huggingface.co/blog/davanstrien/fineweb2-community
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- 3 replies
Post
3821
Commits speak louder than words 🤪
* 4 new video models
* Multiple image models, including SANA & Flux Control
* New quantizers -> GGUF & TorchAO
* New training scripts
Enjoy this holiday-special Diffusers release 🤗
Notes: https://github.com/huggingface/diffusers/releases/tag/v0.32.0
* 4 new video models
* Multiple image models, including SANA & Flux Control
* New quantizers -> GGUF & TorchAO
* New training scripts
Enjoy this holiday-special Diffusers release 🤗
Notes: https://github.com/huggingface/diffusers/releases/tag/v0.32.0
prithivMLmods
posted
an
update
15 days ago
davanstrien
posted
an
update
17 days ago
Post
1697
Introducing FineWeb-C 🌐🎓, a community-built dataset for improving language models in ALL languages.
Inspired by FineWeb-Edu the community is labelling the educational quality of texts for many languages.
318 annotators, 32K+ annotations, 12 languages - and growing! 🌍
data-is-better-together/fineweb-c
Inspired by FineWeb-Edu the community is labelling the educational quality of texts for many languages.
318 annotators, 32K+ annotations, 12 languages - and growing! 🌍
data-is-better-together/fineweb-c
Post
1269
🔍 From instruction-following to creative storytelling, dive into 2024's most impactful AI datasets! These gems are shaping everything from scientific research to video understanding.
Check it out: huggingface/open-source-ai-year-in-review-2024
Check it out: huggingface/open-source-ai-year-in-review-2024
prithivMLmods
posted
an
update
18 days ago
Post
2493
Qwen2VL Models: Vision and Language Processing 🍉
📍FT; [ Latex OCR, Math Parsing, Text Analogy OCRTest ]
Colab Demo: prithivMLmods/Qwen2-VL-OCR-2B-Instruct
❄️Demo : prithivMLmods/Qwen2-VL-2B . The demo includes the Qwen2VL 2B Base Model.
🎯The space handles documenting content from the input image along with standardized plain text. It includes adjustment tools with over 30 font styles, file formatting support for PDF and DOCX, textual alignments, font size adjustments, and line spacing modifications.
📄PDFs are rendered using the ReportLab software library toolkit.
🧵Models :
+ prithivMLmods/Qwen2-VL-OCR-2B-Instruct
+ prithivMLmods/Qwen2-VL-Ocrtest-2B-Instruct
+ prithivMLmods/Qwen2-VL-Math-Prase-2B-Instruct
🚀Sample Document :
+ https://drive.google.com/file/d/1Hfqqzq4Xc-3eTjbz-jcQY84V5E1YM71E/view?usp=sharing
📦Collection :
+ prithivMLmods/vision-language-models-67639f790e806e1f9799979f
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@prithivMLmods 🤗
📍FT; [ Latex OCR, Math Parsing, Text Analogy OCRTest ]
Colab Demo: prithivMLmods/Qwen2-VL-OCR-2B-Instruct
❄️Demo : prithivMLmods/Qwen2-VL-2B . The demo includes the Qwen2VL 2B Base Model.
🎯The space handles documenting content from the input image along with standardized plain text. It includes adjustment tools with over 30 font styles, file formatting support for PDF and DOCX, textual alignments, font size adjustments, and line spacing modifications.
📄PDFs are rendered using the ReportLab software library toolkit.
🧵Models :
+ prithivMLmods/Qwen2-VL-OCR-2B-Instruct
+ prithivMLmods/Qwen2-VL-Ocrtest-2B-Instruct
+ prithivMLmods/Qwen2-VL-Math-Prase-2B-Instruct
🚀Sample Document :
+ https://drive.google.com/file/d/1Hfqqzq4Xc-3eTjbz-jcQY84V5E1YM71E/view?usp=sharing
📦Collection :
+ prithivMLmods/vision-language-models-67639f790e806e1f9799979f
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@prithivMLmods 🤗
- 1 reply
burtenshaw
posted
an
update
18 days ago
Post
2641
People are flexing their end of year stats, so I made this app to show hub stats in a tidy design!
Thanks @Ameeeee and @jfcalvo for the feature from Argilla!
burtenshaw/recap
Thanks @Ameeeee and @jfcalvo for the feature from Argilla!
burtenshaw/recap
- 1 reply
davidberenstein1957
posted
an
update
19 days ago
Post
1349
🐇 Tumble down the AI rabbit hole without any technical knowledge!
Explore AI models on the Hub by a simple and quick search
Demo: davidberenstein1957/transformers-pipeline-playground
Explore AI models on the Hub by a simple and quick search
Demo: davidberenstein1957/transformers-pipeline-playground
prithivMLmods
posted
an
update
19 days ago
Post
3242
🎄 Here Before - Xmas🎅✨
🧑🏻🎄Models
+ [ Xmas 2D Illustration ] : strangerzonehf/Flux-Xmas-Illustration-LoRA
+ [ Xmas 3D Art ] : strangerzonehf/Flux-Xmas-3D-LoRA
+ [ Xmas Chocolate ] : strangerzonehf/Flux-Xmas-Chocolate-LoRA
+ [ Xmas Isometric Kit ] : strangerzonehf/Flux-Xmas-Isometric-Kit-LoRA
+ [ Xmas Realpix ] : strangerzonehf/Flux-Xmas-Realpix-LoRA
+ [ Xmas Anime ] : strangerzonehf/Flux-Anime-Xmas-LoRA
❄️Collections
+ [ Xmas Art ] : strangerzonehf/christmas-pack-6758b199487adafaddb68f82
+ [ Stranger Zone Collection ] : prithivMLmods/stranger-zone-collections-org-6737118adcf2cb40d66d0c7e
🥶Page
+ [ Stranger Zone ] : https://huggingface.co/strangerzonehf
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@prithivMLmods 🤗
🧑🏻🎄Models
+ [ Xmas 2D Illustration ] : strangerzonehf/Flux-Xmas-Illustration-LoRA
+ [ Xmas 3D Art ] : strangerzonehf/Flux-Xmas-3D-LoRA
+ [ Xmas Chocolate ] : strangerzonehf/Flux-Xmas-Chocolate-LoRA
+ [ Xmas Isometric Kit ] : strangerzonehf/Flux-Xmas-Isometric-Kit-LoRA
+ [ Xmas Realpix ] : strangerzonehf/Flux-Xmas-Realpix-LoRA
+ [ Xmas Anime ] : strangerzonehf/Flux-Anime-Xmas-LoRA
❄️Collections
+ [ Xmas Art ] : strangerzonehf/christmas-pack-6758b199487adafaddb68f82
+ [ Stranger Zone Collection ] : prithivMLmods/stranger-zone-collections-org-6737118adcf2cb40d66d0c7e
🥶Page
+ [ Stranger Zone ] : https://huggingface.co/strangerzonehf
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@prithivMLmods 🤗