🚀 Big News! LG AI Research has open-sourced three EXAONE 3.5 models! 32K tokens Long-Context Understanding 🚀 Excels in English and Korean. ✅ 2.4B, 7.8B, and 32B Models: Supports on-device/low-end GPU usage to versatile frontier-level apps! 🚀 Ranked #1 in instruction-following across seven benchmarks. Delivers top-tier performance in instruction following and long-context understanding! LG AI Research's EXAONE 3.5: A Series of Large Language Models for Real-world Use Cases. Explore Now 🔗: 👉 Try the models from Hugging Face collection: https://lnkd.in/gPkjugkN 👉 Read the Blog: https://lnkd.in/gBBxEXBn 👉 Official Gradio space for EXAONE 3.5 (2.4B, 7.8B Models): https://lnkd.in/gvPb-DeJ
Gradio
Software Development
Mountain View, CA 45,791 followers
Machine learning that actually works.
About us
Generate an easy-to-use UI for your ML model, function, or API with only a few lines of code. Integrate directly into your Python notebook, or share a link with anyone. Gradio allows you to quickly create customizable UI components around your TensorFlow or PyTorch models, or even arbitrary Python functions. Mix and match components to support any combination of inputs and outputs. Our core library is free and open-source!
- Website
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https://gradio.app
External link for Gradio
- Industry
- Software Development
- Company size
- 2-10 employees
- Headquarters
- Mountain View, CA
- Type
- Privately Held
Locations
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Primary
Mountain View, CA 94040, US
Employees at Gradio
Updates
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Gradio reposted this
🆕 🤩 Negative Token Merging Performs adversarial guidance directly using images instead of text (i.e. without negative-prompt)! Helps in increasing Output Diversity🔥🔥 Negative Token Merging demos: 💡 Self-hosted Gradio Demo 1 (Using FLUX): https://lnkd.in/gsk46gGz ✨ Gradio Demo 2 (Using SDXL): https://lnkd.in/g9RFCXp3 Build "Negative Token Merging" or NegToMe locally with their official Gradio app: https://lnkd.in/gdDG2WDF
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🆕 🤩 Negative Token Merging Performs adversarial guidance directly using images instead of text (i.e. without negative-prompt)! Helps in increasing Output Diversity🔥🔥 Negative Token Merging demos: 💡 Self-hosted Gradio Demo 1 (Using FLUX): https://lnkd.in/gsk46gGz ✨ Gradio Demo 2 (Using SDXL): https://lnkd.in/g9RFCXp3 Build "Negative Token Merging" or NegToMe locally with their official Gradio app: https://lnkd.in/gdDG2WDF
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Gradio reposted this
🆕 SwiftEdit: Lightning Fast Text-guided Image Editing via 1-step Diffusion 0.23 secs to make edits !!! 🤯 > SwiftEdit is a user-friendly, lightning-fast editing gradio-app that enables instant edits through simple prompts, delivering precise results.👇 Learn more about the project > You can edit facial Identity and expressions via flexible text prompts SwiftEdit for Instant text-guided image editing (in 0.23s)! ✨ Novel contributions: > One-step inversion framework that enables one-step image reconstruction > Mask-guided editing technique to perform localized image editing. SwiftEdit: Lightning Fast Text-guided Image Editing via One-step Diffusion 👉 Useful links: Project: https://lnkd.in/gNVEhW4r Paper: https://lnkd.in/gBQasd-S Code and gradio-app release awaited on Hugging Face, stay tuned! 🤗
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🆕 SwiftEdit: Lightning Fast Text-guided Image Editing via 1-step Diffusion 0.23 secs to make edits !!! 🤯 > SwiftEdit is a user-friendly, lightning-fast editing gradio-app that enables instant edits through simple prompts, delivering precise results.👇 Learn more about the project > You can edit facial Identity and expressions via flexible text prompts SwiftEdit for Instant text-guided image editing (in 0.23s)! ✨ Novel contributions: > One-step inversion framework that enables one-step image reconstruction > Mask-guided editing technique to perform localized image editing. SwiftEdit: Lightning Fast Text-guided Image Editing via One-step Diffusion 👉 Useful links: Project: https://lnkd.in/gNVEhW4r Paper: https://lnkd.in/gBQasd-S Code and gradio-app release awaited on Hugging Face, stay tuned! 🤗
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Gradio reposted this
Efficient Track Anything Model (EfficientTAM) 📣 🔥 Can run >10 frames per second with reasonable video segmentation performance on iPhone 15. Achieves comparable performance with SAM 2 with improved efficiency (⚡ fast!). Uses a vanilla lightweight ViT image encoder. Try the official 🤗Gradio Demo with a family of EfficientTAMs at: https://lnkd.in/gPT5Jc-M Project page: https://lnkd.in/gTMgN4nw Code: https://lnkd.in/g-sCCwyu Models on Hugging Face Hub: https://lnkd.in/gGgaumXd
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📣 Microsoft Research releases Florence-VL, a new family of MLLMs powered by the generative vision foundation model Florence-2. Achieves significant improvements in general VQA, perception, hallucination, OCR, Chart, knowledge-intensive understanding, and more🔥 Useful Hugging Face links to learn more about the model and release:👇 Gradio Multimodal Chat with Florence-VL-8B: https://lnkd.in/gSZbDBbi Florence-VL: Enhancing Vision-Language Models with Generative Vision Encoder and Depth-Breadth Fusion. Paper: https://lnkd.in/grXP_C5b Florence VL 8b SFT Model: https://lnkd.in/gWD5Vhqt
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NVComposer is a breakthrough in generating Novel View Synthesis for given image(s) 🔥 > Choose camera movement mode: Spherical Mode & Translation Mode > You can even adjust the spherical parameters and translations along the X, Y, and Z axes > You can upload up to 4 images as input conditions. > Another solid research by Tencent ARC group!🙌 Gradio app for 📸 NVComposer on Hugging Face Spaces: https://lnkd.in/gV5GtZBF
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Gradio reposted this
Efficient Track Anything Model (EfficientTAM) 📣 🔥 Can run >10 frames per second with reasonable video segmentation performance on iPhone 15. Achieves comparable performance with SAM 2 with improved efficiency (⚡ fast!). Uses a vanilla lightweight ViT image encoder. Try the official 🤗Gradio Demo with a family of EfficientTAMs at: https://lnkd.in/gPT5Jc-M Project page: https://lnkd.in/gTMgN4nw Code: https://lnkd.in/g-sCCwyu Models on Hugging Face Hub: https://lnkd.in/gGgaumXd
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Efficient Track Anything Model (EfficientTAM) 📣 🔥 Can run >10 frames per second with reasonable video segmentation performance on iPhone 15. Achieves comparable performance with SAM 2 with improved efficiency (⚡ fast!). Uses a vanilla lightweight ViT image encoder. Try the official 🤗Gradio Demo with a family of EfficientTAMs at: https://lnkd.in/gPT5Jc-M Project page: https://lnkd.in/gTMgN4nw Code: https://lnkd.in/g-sCCwyu Models on Hugging Face Hub: https://lnkd.in/gGgaumXd