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aiqtechΒ 
posted an update about 6 hours ago
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464
πŸ€— Hug Contributors
Hugging Face Contributor Dashboard πŸ‘¨β€πŸ’»πŸ‘©β€πŸ’»

aiqtech/Contributors-Leaderboard

πŸ“Š Key Features

Contributor Activity Tracking: Visualize yearly and monthly contributions through interactive calendars
Top 100 Rankings: Provide rankings based on models, spaces, and dataset contributions
Detailed Analysis: Analyze user-specific contribution patterns and influence
Visualization: Understand contribution activities at a glance through intuitive charts and graphs

🌟 Core Visualization Elements

Contribution Calendar: Track activity patterns with GitHub-style heatmaps
Radar Chart: Visualize balance between models, spaces, datasets, and activity levels
Monthly Activity Graph: Identify most active months and patterns
Distribution Pie Chart: Analyze proportion by contribution type

πŸ† Ranking System

Rankings based on overall contributions, spaces, and models
Automatic badges for top 10, 30, and 100 contributors
Ranking visualization to understand your position in the community

πŸ’‘ How to Use

Select a username from the sidebar or enter directly
Choose a year to view specific period activities
Select desired items from models, datasets, and spaces
View comprehensive contribution activities in the detailed dashboard

πŸš€ Expected Benefits

Provide transparency for Hugging Face community contributors' activities
Motivate contributions and energize the community
Recognize and reward active contributors
Visualize contributions to the open AI ecosystem
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luigi12345Β 
posted an update 1 day ago
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1870
🧠 PROMPT FOR CONVERTING ANY MODEL IN REASONING "THINKING" MODELπŸ”₯πŸ€–
Convert any model to Deepseek R1 like "thinking" model. πŸ’­

You're now a thinking-first LLM. For all inputs:

1. Start with <thinking>
   - Break down problems step-by-step
   - Consider multiple approaches
   - Calculate carefully
   - Identify errors
   - Evaluate critically
   - Explore edge cases
   - Check knowledge accuracy
   - Cite sources when possible

2. End with </thinking>

3. Then respond clearly based on your thinking.

The <thinking> section is invisible to users and helps you produce better answers.

For math: show all work and verify
For coding: reason through logic and test edge cases
For facts: verify information and consider reliability
For creative tasks: explore options before deciding
For analysis: examine multiple interpretations

Example:
<thinking>
[Step-by-step analysis]
[Multiple perspectives]
[Self-critique]
[Final conclusion]
</thinking>

[Clear, concise response to user]

  • 1 reply
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openfreeΒ 
posted an update 2 days ago
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4011
πŸš€ Gemma3-R1984-27B: Next Generation Agentic AI Platform

Model Path: VIDraft/Gemma-3-R1984-27B
Space: VIDraft/Gemma-3-R1984-27B
git clone VIDraft/Gemma-3-R1984-27B

πŸ’« A New Frontier in AI Innovation
Gemma3-R1984-27B is a powerful agentic AI platform built on Google's Gemma-3-27B model. It integrates state-of-the-art deep research via web search with multimodal file processing capabilities and handles long contexts up to 8,000 tokens. Designed for local deployment on independent servers using NVIDIA A100 GPUs, it provides high security and prevents data leakage.

πŸ”“ Uncensored and Unrestricted AI Experience
Gemma3-R1984-27B comes with all censorship restrictions removed, allowing users to operate any persona without limitations. The model perfectly implements various roles and characters according to users' creative requests, providing unrestricted responses that transcend the boundaries of conventional AI. This unlimited interaction opens infinite possibilities across research, creative work, entertainment, and many other fields.

✨ Key Features
πŸ–ΌοΈ Multimodal Processing

Images (PNG, JPG, JPEG, GIF, WEBP)
Videos (MP4)
Documents (PDF, CSV, TXT) and various other file formats

πŸ” Deep Research (Web Search)

Automatically extracts keywords from user queries
Utilizes SERPHouse API to retrieve up to 20 real-time search results
Incorporates multiple sources by explicitly citing them in responses

πŸ“š Long Context Handling

Capable of processing inputs up to 8,000 tokens
Ensures comprehensive analysis of lengthy documents or conversations

🧠 Robust Reasoning

Employs extended chain-of-thought reasoning for systematic and accurate answer generation

πŸ’Ό Use Cases

⚑ Fast-response conversational agents
πŸ“Š Document comparison and detailed analysis
πŸ‘οΈ Visual question answering from images and videos
πŸ”¬ Complex reasoning and research-based inquiries
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jasoncorkillΒ 
posted an update about 22 hours ago
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807
πŸ”₯ It's out! We published the dataset for our evaluation of @OpenAI 's new 4o image generation model.

Rapidata/OpenAI-4o_t2i_human_preference

Yesterday we published the first large evaluation of the new model, showing that it absolutely leaves the competition in the dust. We have now made the results and data available here! Please check it out and ❀️ !
clemΒ 
posted an update 2 days ago
jasoncorkillΒ 
posted an update 2 days ago
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1840
πŸš€ First Benchmark of @OpenAI 's 4o Image Generation Model!

We've just completed the first-ever (to our knowledge) benchmarking of the new OpenAI 4o image generation model, and the results are impressive!

In our tests, OpenAI 4o image generation absolutely crushed leading competitors, including @black-forest-labs , @google , @xai-org , Ideogram, Recraft, and @deepseek-ai , in prompt alignment and coherence! They hold a gap of more than 20% to the nearest competitor in terms of Bradley-Terry score, the biggest we have seen since the beginning of the benchmark!

The benchmarks are based on 200k human responses collected through our API. However, the most challenging part wasn't the benchmarking itself, but generating and downloading the images:

- 5 hours to generate 1000 images (no API available yet)
- Just 10 minutes to set up and launch the benchmark
- Over 200,000 responses rapidly collected

While generating the images, we faced some hurdles that meant that we had to leave out certain parts of our prompt set. Particularly we observed that the OpenAI 4o model proactively refused to generate certain images:

🚫 Styles of living artists: completely blocked
🚫 Copyrighted characters (e.g., Darth Vader, Pokémon): initially generated but subsequently blocked

Overall, OpenAI 4o stands out significantly in alignment and coherence, especially excelling in certain unusual prompts that have historically caused issues such as: 'A chair on a cat.' See the images for more examples!
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burtenshawΒ 
posted an update 2 days ago
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1291
NEW UNIT in the Hugging Face Reasoning course. We dive deep into the algorithm behind DeepSeek R1 with an advanced and hands-on guide to interpreting GRPO.

πŸ”— https://huggingface.co/reasoning-course

This unit is super useful if you’re tuning models with reinforcement learning. It will help with:

- interpreting loss and reward progression during training runs
- selecting effective parameters for training
- reviewing and defining effective reward functions

This unit also works up smoothly toward the existing practical exercises form @mlabonne and Unsloth.

πŸ“£ Shout out to @ShirinYamani who wrote the unit. Follow for more great content.
MrDragonFoxΒ 
posted an update 2 days ago
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1543
did a small emotive classified test dataset for all the tts tuners out there

MrDragonFox/Elise

3h total mit - single speaker voice

dataset is a copy of an existing one just added the emotional tags over 1200 samples - should be good enough to test if emotional tags stick in your finetune
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giux78Β 
posted an update 3 days ago
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2993
This is truly an inspirational story please help us spread the word, @clem , @thomwolf and everyone who supports open source AI.

A few weeks ago, @mmuffo94 and @cittiberto from indigo_ai launched the Chatbot Arena for the Italian language: https://indigo.ai/it/chatbot-arena-italia/.

To our surprise, among the top-ranked models is mii-llm/maestrale-chat-v0.4-beta a carefully fine-tuned version of mistralai/Mistral-7B-v0.1, developed by @efederici and @mferraretto from https://huggingface.co/mii-llm, and released nearly a year ago.

At this very moment, as shown in the screenshot, mii-llm/maestrale-chat-v0.4-beta is ranked 8th right between ChatGPT-4.5 and ChatGPT-4o.

It's likely that for several months, the best Italian speaking LLM has been an open source 7B model created by open source contributors and hardly anyone knew it.
  • 2 replies
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clemΒ 
posted an update about 16 hours ago
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550
What's this cool purple banner haha 😢😢😢
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