linoyts (Linoy Tsaban)

reacted to AdinaY's post with 🔥 10 minutes ago

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Kimi-Audio 🚀🎧 an OPEN audio foundation model released by Moonshot AI
moonshotai/Kimi-Audio-7B-Instruct
✨ 7B
✨ 13M+ hours of pretraining data
✨ Novel hybrid input architecture
✨ Universal audio capabilities (ASR, AQA, AAC, SER, SEC/ASC, end-to-end conversation)

reacted to luigi12345's post with 🔥 4 days ago

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SkyReels-V2 INFINITE VIDEO🔥♾️🎬 UNLIMITED duration video generation model by Skywork.

> “Finally is here. An Open-Source model that achieves what we all have waiting for: Infinite Length Videos.’’😮

Skywork R1V: Pioneering Multimodal Reasoning with Chain-of-Thought (2504.05599)

Model: Skywork/SkyReels-V2-T2V-14B-720P

✨ 1.3B & 14B
✨ Generates infinite length videos using Diffusion Forcing with diffusion models + autoregressive methods

reacted to victor's post with 👍 4 days ago

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DIA TTS is just amazing - please share your funniest gens (here is mine) 😂
nari-labs/Dia-1.6B

reacted to AdinaY's post with 🔥 5 days ago

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MAGI-1 🪄 the autoregressive diffusion video model, released by Sand AI

sand-ai/MAGI-1

✨ 24B with Apache 2.0
✨ Strong temporal consistency
✨ Benchmark-topping performance

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posted an update 6 days ago

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We just shipped HiDream Image LoRA fine-tuning to diffusers🧨

HiDream's sota capabilities (and mit license) bring a lot of potential to explore with fine-tunes 🔥

- more upgrades and features soon!
- code, weights and config example 👇

🧶Yarn art lora: linoyts/HiDream-yarn-art-LoRA
code: https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_hidream.md

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reacted to fdaudens's post with 🤯 18 days ago

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🎨 Designers, meet OmniSVG! This new model helps you create professional vector graphics from text/images, generate editable SVGs from icons to detailed characters, convert rasters to vectors, maintain style consistency with references, and integrate into your workflow.

@OmniSVG

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reacted to ajibawa-2023's post with 🔥 18 days ago

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Hi All, I recently released two Audio datasets which are generated using my earlier released dataset: ajibawa-2023/Children-Stories-Collection

First Audio Dataset:https://huggingface.co/datasets/ajibawa-2023/Audio-Children-Stories-Collection-Large has 5600++ stories in .mp3 format.

Second Audio Dataset:https://huggingface.co/datasets/ajibawa-2023/Audio-Children-Stories-Collection has 600 stories in .mp3 format.

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reacted to AdinaY's post with 🔥 24 days ago

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SkyReels-A2 🚀 an open framework for controllable video generation from text + images, released by Skywork, KunLun

✨Model:
Skywork/SkyReels-A2
✨Paper:
SkyReels-A2: Compose Anything in Video Diffusion Transformers (2504.02436)

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reacted to seawolf2357's post with 🔥 25 days ago

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🎨 Ghibli-Style Image Generation with Multilingual Text Integration: FLUX.1 Hugging Face Edition 🌏✨

Hello creators! Today I'm introducing a special image generator that combines the beautiful aesthetics of Studio Ghibli with multilingual text integration! 😍

seawolf2357/Ghibli-Multilingual-Text-rendering

✨ Key Features

Ghibli-Style Image Generation - High-quality animation-style images based on FLUX.1
Multilingual Text Rendering - Support for Korean, Japanese, English, and all languages! 🇰🇷🇯🇵🇬🇧
Automatic Image Editing with Simple Prompts - Just input your desired text and you're done!
Two Stylistic Variations Provided - Get two different results from a single prompt
Full Hugging Face Spaces Support - Deploy and share instantly!

🚀 How Does It Work?

Enter a prompt describing your desired image (e.g., "a cat sitting by the window")
Input the text you want to add (any language works!)
Select the text position, size, and color
Two different versions are automatically generated!

💯 Advantages of This Model

No Tedious Post-Editing Needed - Text is perfectly integrated during generation
Natural Text Integration - Text automatically adjusts to match the image style
Perfect Multilingual Support - Any language renders beautifully!
User-Friendly Interface - Easily adjust text size, position, and color
One-Click Hugging Face Deployment - Use immediately without complex setup

🎭 Use Cases

Creating multilingual greeting cards
Animation-style social media content
Ghibli-inspired posters or banners
Character images with dialogue in various languages
Sharing with the community through Hugging Face Spaces

This project leverages Hugging Face's FLUX.1 model to open new possibilities for seamlessly integrating high-quality Ghibli-style images with multilingual text using just prompts! 🌈
Try it now and create your own artistic masterpieces! 🎨✨

#GhibliStyle #MultilingualSupport #AIImageGeneration #TextRendering #FLUX #HuggingFace

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reacted to ZhiyuanthePony's post with 🤗 27 days ago

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🎉 Thrilled to share our #CVPR2025 accepted work:
Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Data (2503.21694)

🔥 Key Innovations:
1️⃣ First to adapt SD for direct textured mesh generation (1-2s inference)
2️⃣ Novel teacher-student framework leveraging multi-view diffusion models ([MVDream](https://arxiv.org/abs/2308.16512) & [RichDreamer](https://arxiv.org/abs/2311.16918))
3️⃣ Parameter-efficient tuning - only +2.6% params over base SD
4️⃣ 3D data-free training liberates model from dataset constraints

💡 Why matters?
→ A novel 3D-Data-Free paradigm
→ Outperforms data-driven methods on creative concept generation
→ Unlocks web-scale text corpus for 3D content creation

🌐 Project: https://theericma.github.io/TriplaneTurbo/
🎮 Demo: ZhiyuanthePony/TriplaneTurbo
💻 Code: https://github.com/theEricMa/TriplaneTurbo

reacted to prithivMLmods's post with 👍 about 1 month ago

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Dropping Downstream tasks using newly initialized parameters and weights ([classifier.bias & weights]) support domain-specific 𝗶𝗺𝗮𝗴𝗲 𝗰𝗹𝗮𝘀𝘀𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻. Based on siglip2-base-patch16-224 and DomainNet (single-domain, multi-source adaptation), with Fashion-MNIST & More for experimental testing. 🧤☄️

Fashion-Mnist : prithivMLmods/Fashion-Mnist-SigLIP2
Mnist-Digits : prithivMLmods/Mnist-Digits-SigLIP2
Multisource-121 : prithivMLmods/Multisource-121-DomainNet
Painting-126 : prithivMLmods/Painting-126-DomainNet
Sketch-126 : prithivMLmods/Sketch-126-DomainNet
Clipart-126 : prithivMLmods/Clipart-126-DomainNet

Models are trained with different parameter settings for experimental purposes only, with the intent of further development. Refer to the model page below for instructions on running it with Transformers 🤗.

Collection : prithivMLmods/domainnet-0324-67e0e3c934c03cc40c6c8782

Citations : SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features https://arxiv.org/pdf/2502.14786 & Moment Matching for Multi-Source Domain Adaptation : https://arxiv.org/pdf/1812.01754

reacted to Yehor's post with 👍 about 2 months ago

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Published a stable version of Ukrainian Text-to-Speech library on GitHub and PyPI.

Features:

- Multi-speaker model: 2 female (Tetiana, Lada) + 1 male (Mykyta) voices;
- Fine-grained control over speech parameters, including duration, fundamental frequency (F0), and energy;
- High-fidelity speech generation using the RAD-TTS++ acoustic model;
- Fast vocoding using Vocos;
- Synthesizes long sentences effectively;
- Supports a sampling rate of 44.1 kHz;
- Tested on Linux environments and Windows/WSL;
- Python API (requires Python 3.9 or later);
- CUDA-enabled for GPU acceleration.

Repository: https://github.com/egorsmkv/tts_uk

reacted to freddyaboulton's post with 🚀 2 months ago

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Getting WebRTC and Websockets right in python is very tricky. If you've tried to wrap an LLM in a real-time audio layer then you know what I'm talking about.

That's where FastRTC comes in! It makes WebRTC and Websocket streams super easy with minimal code and overhead.

Check out our org: hf.co/fastrtc

reacted to burtenshaw's post with 🔥 2 months ago

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Now the Hugging Face agent course is getting real! With frameworks like smolagents, LlamaIndex, and LangChain.

🔗 Follow the org for updates

agents-course

This week we are releasing the first framework unit in the course and it’s on smolagents. This is what the unit covers:

- why should you use smolagents vs another library?
- how to build agents that use code
- build multiagents systems
- use vision language models for browser use

The team has been working flat out on this for a few weeks. Led by @sergiopaniego and supported by smolagents author @m-ric .

reacted to AdinaY's post with ❤️ 2 months ago

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🚀 StepFun阶跃星辰 is making BIG open moves!

Last year, their GOT-OCR 2.0 took the community by storm 🔥but many didn’t know they were also building some amazing models. Now, they’ve just dropped something huge on the hub!

📺 Step-Video-T2V: a 30B bilingual open video model that generates 204 frames (8-10s) at 540P resolution with high information density & consistency.
stepfun-ai/stepvideo-t2v

🔊 Step-Audio-TTS-3B : a TTS trained with the LLM-Chat paradigm on a large synthetic dataset, capable of generating RAP & Humming
stepfun-ai/step-audio-67b33accf45735bb21131b0b

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reacted to davidberenstein1957's post with 🤗 3 months ago

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Creating an agentic RAG stack on the Hugging Face Hub - part 1 - retrieval (1/5).

🚀 Web apps and microservices included!

Chunk, embed and index documents at a huge scale without overhead.

Blog: https://huggingface.co/blog/davidberenstein1957/ai-blueprint-agentic-rag-part-1-retrieve

reacted to not-lain's post with 🔥 3 months ago

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I have just released a new blogpost about kv caching and its role in inference speedup 🚀
🔗 https://huggingface.co/blog/not-lain/kv-caching/
some takeaways :

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reacted to burtenshaw's post with 🔥 3 months ago

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We’re launching a FREE and CERTIFIED course on Agents!

We're thrilled to announce the launch of the Hugging Face Agents course on Learn! This interactive, certified course will guide you through building and deploying your own AI agents.

Here's what you'll learn:

- Understanding Agents: We'll break down the fundamentals of AI agents, showing you how they use LLMs to perceive their environment (observations), reason about it (thoughts), and take actions. Think of a smart assistant that can book appointments, answer emails, or even write code based on your instructions.
- Building with Frameworks: You'll dive into popular agent frameworks like LangChain, LlamaIndex and smolagents. These tools provide the building blocks for creating complex agent behaviors.
- Real-World Applications: See how agents are used in practice, from automating SQL queries to generating code and summarizing complex documents.
- Certification: Earn a certification by completing the course modules, implementing a use case, and passing a benchmark assessment. This proves your skills in building and deploying AI agents.
Audience

This course is designed for anyone interested in the future of AI. Whether you're a developer, data scientist, or simply curious about AI, this course will equip you with the knowledge and skills to build your own intelligent agents.

Enroll today and start building the next generation of AI agent applications!

https://bit.ly/hf-learn-agents

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reacted to alibabasglab's post with 🔥 3 months ago

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We are thrilled to present the improved "ClearerVoice-Studio", an open-source platform designed to make speech processing easy use for everyone! Whether you’re working on speech enhancement, speech separation, speech super-resolution, or target speaker extraction, this unified platform has you covered.

** Why Choose ClearerVoice-Studio?**

- Pre-Trained Models: Includes cutting-edge pre-trained models, fine-tuned on extensive, high-quality datasets. No need to start from scratch!
- Ease of Use: Designed for seamless integration with your projects, offering a simple yet flexible interface for inference and training.

**Where to Find Us?**

- GitHub Repository: ClearerVoice-Studio (https://github.com/modelscope/ClearerVoice-Studio)
- Try Our Demo: Hugging Face Space ( alibabasglab/ClearVoice)

**What Can You Do with ClearerVoice-Studio?**

- Enhance noisy speech recordings to achieve crystal-clear quality.
- Separate speech from complex audio mixtures with ease.
- Transform low-resolution audio into high-resolution audio. A full upscaled LJSpeech-1.1-48kHz dataset can be downloaded from alibabasglab/LJSpeech-1.1-48kHz .
- Extract target speaker voices with precision using audio-visual models.

**Join Us in Growing ClearerVoice-Studio!**

We believe in the power of open-source collaboration. By starring our GitHub repository and sharing ClearerVoice-Studio with your network, you can help us grow this community-driven platform.

**Support us by:**

- Starring it on GitHub.
- Exploring and contributing to our codebase .
- Sharing your feedback and use cases to make the platform even better.
- Joining our community discussions to exchange ideas and innovations.
- Together, let’s push the boundaries of speech processing! Thank you for your support! :sparkling_heart:

reacted to Tonic's post with 🔥 3 months ago

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🙋🏻‍♂️Hey there folks , Open LLM Europe just released Lucie 7B-Instruct model , a billingual instruct model trained on open data ! You can check out my unofficial demo here while we wait for the official inference api from the group : Tonic/Lucie-7B hope you like it 🚀

Linoy Tsaban

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