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Leaderboard Retos Hackathon SomosNLP 2025
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Leaderboard Retos Hackathon SomosNLP 2025
SomosNLP
non-profit
AI & ML interests
Democratizar el PLN en español e incentivar su aplicación para generar impacto social 💛
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mariagrandury
updated
a
Space
29 days ago
Post
3223
A few months ago, I shared that I was building with
@deeivihh
something like "the Steam for open source apps"...
🚀 Today, I’m excited to announce that Dione is now open source and live in public beta!
Our mission is simple: make it easier to discover, use, and contribute to open source applications.
🔗 GitHub: https://github.com/dioneapp/dioneapp
💬 Join the community: https://discord.gg/JDFJp33vrM
Want to give it a try? I’d love your feedback! 👀
🚀 Today, I’m excited to announce that Dione is now open source and live in public beta!
Our mission is simple: make it easier to discover, use, and contribute to open source applications.
🔗 GitHub: https://github.com/dioneapp/dioneapp
💬 Join the community: https://discord.gg/JDFJp33vrM
Want to give it a try? I’d love your feedback! 👀
mariagrandury
published
a
dataset
3 months ago
dvilasuero
posted
an
update
3 months ago
Post
2865
Super excited to launch Hugging Face Sheets: Spreadsheets meet AI and unstructured data.
A few months ago, we started imagining new ways to build and transform datasets with the latest open-source models.
Today, I'm thrilled to introduce our first step in this direction.
In a nutshell:
📁 Effortlessly run prompts and models over your data.
🌐 Agentic search for accuracy and real-time information.
🖼️ Familiar, minimalistic interface for interacting with data.
🎯 Human feedback 2.0: Your input directly improves generated data.
💯 Access hundreds of open models and leading inference providers.
Go to this space to try it out!
aisheets/sheets
Leave your questions below, we're just getting started!
A few months ago, we started imagining new ways to build and transform datasets with the latest open-source models.
Today, I'm thrilled to introduce our first step in this direction.
In a nutshell:
📁 Effortlessly run prompts and models over your data.
🌐 Agentic search for accuracy and real-time information.
🖼️ Familiar, minimalistic interface for interacting with data.
🎯 Human feedback 2.0: Your input directly improves generated data.
💯 Access hundreds of open models and leading inference providers.
Go to this space to try it out!
aisheets/sheets
Leave your questions below, we're just getting started!
-
- 3 replies
dianags
authored
2
papers
3 months ago
mariagrandury
authored
2
papers
4 months ago
How use the dataset to train my model GPT
2
#1 opened 4 months ago
by
luisaarias
lewtun
authored
a
paper
4 months ago
Post
4505
Today we launch Dione.
A few months ago it was just a wild idea I shared with @bygimenez , now it's real.
Dione (Beta) is here, the easiest way to discover and install open-source apps, especially AI ones.
Think of it as the Steam of open source. Installing open-source tools is often a mess. Dione fixes that.
Beautiful UI and workflow. Soon multi-platform, multilingual & fully open-source.
Users can even write and share their own installation scripts. This is just the beginning.
🚀 Join our exclusive Beta
→ https://getdione.app/beta/join
A few months ago it was just a wild idea I shared with @bygimenez , now it's real.
Dione (Beta) is here, the easiest way to discover and install open-source apps, especially AI ones.
Think of it as the Steam of open source. Installing open-source tools is often a mess. Dione fixes that.
Beautiful UI and workflow. Soon multi-platform, multilingual & fully open-source.
Users can even write and share their own installation scripts. This is just the beginning.
🚀 Join our exclusive Beta
→ https://getdione.app/beta/join
- 2 replies
ouhenio
updated
a
Space
5 months ago
lewtun
authored
a
paper
5 months ago
lewtun
authored
a
paper
6 months ago
Post
3411
Introducing OlympicCoder: a series of open reasoning models that can solve olympiad-level programming problems 🧑💻
- 7B open-r1/OlympicCoder-7B
- 32B open-r1/OlympicCoder-32B
We find that OlympicCoder models outperform Claude 3.7 Sonnet, as well as others over 100x larger 💪
Together with the models, we are releasing:
📊CodeForces-CoTs: new dataset of code problems from the most popular competitive coding platform, with R1 traces in C++ and Python open-r1/codeforces-cots
🏆 IOI'2024: a new benchmark of VERY hard programming problems where even frontier models struggle to match human performance open-r1/ioi
For links to the models and datasets, check out our latest progress report from Open R1: https://huggingface.co/blog/open-r1/update-3
- 7B open-r1/OlympicCoder-7B
- 32B open-r1/OlympicCoder-32B
We find that OlympicCoder models outperform Claude 3.7 Sonnet, as well as others over 100x larger 💪
Together with the models, we are releasing:
📊CodeForces-CoTs: new dataset of code problems from the most popular competitive coding platform, with R1 traces in C++ and Python open-r1/codeforces-cots
🏆 IOI'2024: a new benchmark of VERY hard programming problems where even frontier models struggle to match human performance open-r1/ioi
For links to the models and datasets, check out our latest progress report from Open R1: https://huggingface.co/blog/open-r1/update-3
- 1 reply
Post
5442
Introducing OpenR1-Math-220k!
open-r1/OpenR1-Math-220k
The community has been busy distilling DeepSeek-R1 from inference providers, but we decided to have a go at doing it ourselves from scratch 💪
What’s new compared to existing reasoning datasets?
♾ Based on AI-MO/NuminaMath-1.5: we focus on math reasoning traces and generate answers for problems in NuminaMath 1.5, an improved version of the popular NuminaMath-CoT dataset.
🐳 800k R1 reasoning traces: We generate two answers for 400k problems using DeepSeek R1. The filtered dataset contains 220k problems with correct reasoning traces.
📀 512 H100s running locally: Instead of relying on an API, we leverage vLLM and SGLang to run generations locally on our science cluster, generating 180k reasoning traces per day.
⏳ Automated filtering: We apply Math Verify to only retain problems with at least one correct answer. We also leverage Llama3.3-70B-Instruct as a judge to retrieve more correct examples (e.g for cases with malformed answers that can’t be verified with a rules-based parser)
📊 We match the performance of DeepSeek-Distill-Qwen-7B by finetuning Qwen-7B-Math-Instruct on our dataset.
🔎 Read our blog post for all the nitty gritty details: https://huggingface.co/blog/open-r1/update-2
open-r1/OpenR1-Math-220k
The community has been busy distilling DeepSeek-R1 from inference providers, but we decided to have a go at doing it ourselves from scratch 💪
What’s new compared to existing reasoning datasets?
♾ Based on AI-MO/NuminaMath-1.5: we focus on math reasoning traces and generate answers for problems in NuminaMath 1.5, an improved version of the popular NuminaMath-CoT dataset.
🐳 800k R1 reasoning traces: We generate two answers for 400k problems using DeepSeek R1. The filtered dataset contains 220k problems with correct reasoning traces.
📀 512 H100s running locally: Instead of relying on an API, we leverage vLLM and SGLang to run generations locally on our science cluster, generating 180k reasoning traces per day.
⏳ Automated filtering: We apply Math Verify to only retain problems with at least one correct answer. We also leverage Llama3.3-70B-Instruct as a judge to retrieve more correct examples (e.g for cases with malformed answers that can’t be verified with a rules-based parser)
📊 We match the performance of DeepSeek-Distill-Qwen-7B by finetuning Qwen-7B-Math-Instruct on our dataset.
🔎 Read our blog post for all the nitty gritty details: https://huggingface.co/blog/open-r1/update-2
plaguss
authored
a
paper
7 months ago
lewtun
authored
a
paper
7 months ago
mariagrandury
updated
2
collections
7 months ago