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aiqtechΒ 
posted an update about 23 hours ago
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1840
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 2 days ago
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2714
🧠 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]

  • 3 replies
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jasoncorkillΒ 
posted an update 1 day ago
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1548
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 ❀️ !
openfreeΒ 
posted an update 3 days ago
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4303
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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AdinaYΒ 
posted an update 1 day ago
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1332
Let's check out the latest releases from the Chinese community in March!

πŸ‘‰ https://huggingface.co/collections/zh-ai-community/march-2025-releases-from-the-chinese-community-67c6b479ebb87abbdf8e2e76


✨MLLM
> R1 Omni by Alibaba Tongyi - 0.5B
> Qwen2.5 Omni by Alibaba Qwen - 7B with apache2.0

πŸ–ΌοΈVideo
> CogView-4 by ZhipuAI - Apacha2.0
> HunyuanVideo-I2V by TencentHunyuan
> Open Sora2.0 - 11B with Apache2.0
> Stepvideo TI2V by StepFun AI - 30B with MIT license

🎡Audio
> DiffDiffRhythm - Apache2.0
> Spark TTS by SparkAudio - 0.5B

⚑️Image/3D
> Hunyuan3D 2mv/2mini (0.6B) by @TencentHunyuan
> FlexWorld by ByteDance - MIT license
> Qwen2.5-VL-32B-Instruct by Alibaba Qwen - Apache2.0
> Tripo SG (1.5B)/SF by VastAIResearch - MIT license
> InfiniteYou by ByteDance

> LHM by Alibaba AIGC team - Apache2.0
> Spatial LM by ManyCore

🧠Reasoning
> QwQ-32B by Alibaba Qwen - Apache2.0
> Skywork R1V - 38B with MIT license
> RWKV G1 by RWKV AI - 0.1B pure RNN reasoning model with Apache2.0
> Fin R1 by SUFE AIFLM Lab - financial reasoning

πŸ” LLM
> DeepSeek v3 0324 by DeepSeek -MIT license
> Babel by Alibaba DAMO - 9B/83B/25 languages
  • 2 replies
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clemΒ 
posted an update 1 day ago
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1264
What's this cool purple banner haha 😢😢😢
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KeltezaaΒ 
posted an update 2 days ago
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1826
Dear HF Staff and pro Users.

Why did you remove the "Regen" feature from the ZeroGPU feature?
Is this an error or intended?

I am now limited to 13 images per 24 hrs. Using my space.
When I upgraded to Pro, it was exclusively for the 5x more usage and the faster regen.

The reason I spend my hard earned money on your site was for this feature.
This is totally unacceptable.

########
Other Pro Users please reply and tag others
IF YOU AGREE or DISAGREE.
########
@Always-cheating ,@anonymous111110987654321 ,@Arshili @bedspirit @blackedguy @John6666 ,@DavidBaloches @E-07 ,@f-14 @mindfulpeoples @multimodalart
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burtenshawΒ 
posted an update 3 days ago
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1527
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.
  • 1 reply
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ritvik77Β 
posted an update 1 day ago
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1234
ritvik77/ContributionChartHuggingFace
It's Ready!

One feature Hugging Face could really benefit from is a contribution heatmap β€” a visual dashboard to track user engagement and contributions across models, datasets, and models over the year, similar to GitHub’s contribution graph. Guess what, Clem Delangue mentioned idea about using HF API reference for it and we made it for use.

If you are a Hugging Face user add this Space in your collection and it will give you all stats about your contributions and commits nearly same as GitHub. It's still a prototype and still working on it as a product feature.
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onekqΒ 
posted an update 1 day ago
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1117
Open source models are immutable, this is a big pain.

When you open source a piece of software, users leave their feedbacks via issues or PRs. You can merge their feedbacks in semi real time, this creates a positive cycle. Then you have a community.

LLMs don't have these nice micro steps. There are no hot fixes. Even a minor version bump is an endeavor. I'm quite confident my model is being used by teams somewhere. But until next launch, it's awfully quiet.

I don't know the solution. Just a regular lament before weekend. πŸ€—

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