RANGER: A Monocular Zero-Shot Semantic Navigation Framework through Contextual Adaptation
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tellarin
authored
2
papers
3 days ago
prithivMLmods
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an
update
4 days ago
Post
704
GLM OCR, a multimodal OCR model for complex document understanding, built on the GLM-V encoder–decoder architecture. It delivers high accuracy and strong generalization with a blazing-fast inference pipeline. The demo is live . Try it now. 🤗🚀
✨ Demo: prithivMLmods/GLM-OCR-Demo
✨ Multimodal Implementations: https://huggingface.co/collections/prithivMLmods/multimodal-implementations
✨ GitHub: https://github.com/PRITHIVSAKTHIUR/GLM-OCR-Demo
✨ Demo: prithivMLmods/GLM-OCR-Demo
✨ Multimodal Implementations: https://huggingface.co/collections/prithivMLmods/multimodal-implementations
✨ GitHub: https://github.com/PRITHIVSAKTHIUR/GLM-OCR-Demo
azminetoushikwasi
submitted
a
paper
to Daily Papers
4 days ago
tellarin
submitted
a
paper
to Daily Papers
4 days ago
Sri-Vigneshwar-DJ
posted
an
update
4 days ago
Post
1339
Just released a new dataset designed for training reasoning models on Meta (Facebook/Instagram) advertising fatigue detection!
What is it? A GRPO (Group Relative Policy Optimization) training dataset with 200+ carefully crafted scenarios covering:
🔍 Fatigue Signal Detection: CTR drops, CPM spikes, frequency analysis
🩺 Performance Diagnosis: Root cause analysis frameworks
📋 Strategy: Creative refresh cadence, testing frameworks
📊 Analysis: ROI calculations, metric interpretation
Why GRPO? GRPO training helps models learn structured reasoning. Each response follows the <thinking> and <answer> format.
Check it out here: Sri-Vigneshwar-DJ/meta-fatigue-grpo-dataset
What is it? A GRPO (Group Relative Policy Optimization) training dataset with 200+ carefully crafted scenarios covering:
🔍 Fatigue Signal Detection: CTR drops, CPM spikes, frequency analysis
🩺 Performance Diagnosis: Root cause analysis frameworks
📋 Strategy: Creative refresh cadence, testing frameworks
📊 Analysis: ROI calculations, metric interpretation
Why GRPO? GRPO training helps models learn structured reasoning. Each response follows the <thinking> and <answer> format.
Check it out here: Sri-Vigneshwar-DJ/meta-fatigue-grpo-dataset
prithivMLmods
posted
an
update
5 days ago
Post
2082
Introducing the Qwen-Image-Edit-3D-Lighting-Control app, featuring 8× horizontal and 3× elevational lighting positions for precise 3D lighting control. It enables studio-level lighting using fast Qwen Image Edit fast inference, paired with Multi-Angle-Lighting adapters. 🔦
🔥 Space: prithivMLmods/Qwen-Image-Edit-3D-Lighting-Control
✅ Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
📂 GitHub: https://github.com/PRITHIVSAKTHIUR/Qwen-Image-Edit-3D-Lighting-Control
🔥 Space: prithivMLmods/Qwen-Image-Edit-3D-Lighting-Control
✅ Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
📂 GitHub: https://github.com/PRITHIVSAKTHIUR/Qwen-Image-Edit-3D-Lighting-Control
prithivMLmods
posted
an
update
10 days ago
Post
3588
Daggr UI version of the Qwen3-TTS demo.🔥
(custom voice, voice design, qwen3-asr and voice cloning) nodes.
No remote spaces used for API inference; all functions run in-app
Powered by t4-m and built with [email protected] and gradio@6.
👉Demo: prithivMLmods/Qwen3-TTS-Daggr-UI
⭐Github: https://github.com/PRITHIVSAKTHIUR/Qwen3-TTS-Daggr-UI
(custom voice, voice design, qwen3-asr and voice cloning) nodes.
No remote spaces used for API inference; all functions run in-app
fn.Powered by t4-m and built with [email protected] and gradio@6.
👉Demo: prithivMLmods/Qwen3-TTS-Daggr-UI
⭐Github: https://github.com/PRITHIVSAKTHIUR/Qwen3-TTS-Daggr-UI
- 1 reply
prithivMLmods
posted
an
update
13 days ago
Post
2665
Qwen-Image-Edit-Object-Manipulator Space is now featured in Hugging Face Space of the Week. It enables object manipulation such as extracting objects, adding designs, and removing objects or designs from the red highlighted area using specialized adapters.
🔥Do enjoy the demo! ~ prithivMLmods/Qwen-Image-Edit-Object-Manipulator
Collections:
🧨Adapters-1: https://huggingface.co/collections/prithivMLmods/qwen-image-edit-exps
🧨Adapters-2: https://huggingface.co/collections/prithivMLmods/qie-jan-23-26
🧨Adapters-3: https://huggingface.co/collections/prithivMLmods/qwen-image-edit-object-manipulator
⭐Github: https://github.com/PRITHIVSAKTHIUR/Qwen-Image-Edit-Object-Manipulator
To learn more, visit the app page or the respective model pages.
🔥Do enjoy the demo! ~ prithivMLmods/Qwen-Image-Edit-Object-Manipulator
Collections:
🧨Adapters-1: https://huggingface.co/collections/prithivMLmods/qwen-image-edit-exps
🧨Adapters-2: https://huggingface.co/collections/prithivMLmods/qie-jan-23-26
🧨Adapters-3: https://huggingface.co/collections/prithivMLmods/qwen-image-edit-object-manipulator
⭐Github: https://github.com/PRITHIVSAKTHIUR/Qwen-Image-Edit-Object-Manipulator
To learn more, visit the app page or the respective model pages.
Sri-Vigneshwar-DJ
posted
an
update
14 days ago
Post
196
🏙️ Hugging Face Community Post
Title: 🧬 Experimenting with "Dynamic Chaos" in Tamil SLMs
Hi everyone! I just published a new experimental study on Small Language Model (SLM) resilience.
I took the Qwen2.5-0.5B model and put it through a "Chaos Phase" to see how much weight data a tiny model can lose before its understanding of classical Tamil grammar breaks.
Key highlights of the study:
Target Data: Fine-tuned on the Thirukkural (1,330 couplets + modern explanations).
The Chaos Step: Applied 20% random weight pruning but implemented "Layer Protection" for the Token Embeddings and LM Head to keep the characters readable.
Compression: 4-bit (Q4_K_M) quantization for extreme efficiency.
Result: A surrealist classical Tamil model that is ultra-light (~300MB) and ultra-fast!
Check out the model and the experiment logic here: Sri-Vigneshwar-DJ/qwen-tamil-chaos-v1
Title: 🧬 Experimenting with "Dynamic Chaos" in Tamil SLMs
Hi everyone! I just published a new experimental study on Small Language Model (SLM) resilience.
I took the Qwen2.5-0.5B model and put it through a "Chaos Phase" to see how much weight data a tiny model can lose before its understanding of classical Tamil grammar breaks.
Key highlights of the study:
Target Data: Fine-tuned on the Thirukkural (1,330 couplets + modern explanations).
The Chaos Step: Applied 20% random weight pruning but implemented "Layer Protection" for the Token Embeddings and LM Head to keep the characters readable.
Compression: 4-bit (Q4_K_M) quantization for extreme efficiency.
Result: A surrealist classical Tamil model that is ultra-light (~300MB) and ultra-fast!
Check out the model and the experiment logic here: Sri-Vigneshwar-DJ/qwen-tamil-chaos-v1
Post
2112
📢 New release! World_events Dataset now available featuring global events spanning 2023 through 2025
🌍 https://huggingface.co/collections/Reubencf/world-events
🚀 2026 dataset dropping soon
🌍 https://huggingface.co/collections/Reubencf/world-events
🚀 2026 dataset dropping soon
- 1 reply
prithivMLmods
posted
an
update
16 days ago
Post
3024
Introducing QIE-2511-Zoom-Master for highlight-guided area zoom-in, enabling lossless zooming within a drawn square area, and QIE-2511-Object-Remover-v2 for precise object or highlight-guided area cleanup. These experimental adapters are trained based on QIE-2511. Find the adapters below.
🕹️QIE-2511-Zoom-Master : prithivMLmods/QIE-2511-Zoom-Master
🕹️QIE-2511-Object-Remover-v2: prithivMLmods/QIE-2511-Object-Remover-v2
🤗Demo: prithivMLmods/Qwen-Image-Edit-Object-Manipulator
📂Collection: https://huggingface.co/collections/prithivMLmods/qwen-image-edit-exps
To learn more, visit the app page or the respective model pages.
🕹️QIE-2511-Zoom-Master : prithivMLmods/QIE-2511-Zoom-Master
🕹️QIE-2511-Object-Remover-v2: prithivMLmods/QIE-2511-Object-Remover-v2
🤗Demo: prithivMLmods/Qwen-Image-Edit-Object-Manipulator
📂Collection: https://huggingface.co/collections/prithivMLmods/qwen-image-edit-exps
To learn more, visit the app page or the respective model pages.
- 2 replies
Post
1816
Now Live: The
Reubencf/Nano_Banana_Editor now includes 10 free requests/day! 🍌 I'm personally sponsoring these credits to help make open AI accessible to all.
(Note: Limits are subject to change based on funding).
Enjoy !
(Note: Limits are subject to change based on funding).
Enjoy !
BounharAbdelaziz
authored
a
paper
19 days ago
BounharAbdelaziz
submitted
a
paper
to Daily Papers
19 days ago
Post
1045
TranslateGemma: Open Translation Models (Jan 2026)
Google introduces TranslateGemma, a new suite of open translation models based on Gemma 3, available in 4B, 12B, and 27B parameter sizes.
Key Highlights:
• Supports 55 languages with high-quality translation across high-, mid-, and low-resource languages
• Exceptional efficiency: 12B model outperforms 27B baseline on WMT24++ benchmark
• Built using two-stage fine-tuning process distilling knowledge from Gemini models
• Retains strong multimodal capabilities (can translate text within images)
• Trained on nearly 500 additional language pairs for research adaptation
• Designed for diverse deployment environments from mobile to cloud
The models achieve state-of-the-art performance while maintaining exceptional efficiency, making high-quality translation accessible across different devices and use cases.
https://huggingface.co/collections/google/translategemma
Google introduces TranslateGemma, a new suite of open translation models based on Gemma 3, available in 4B, 12B, and 27B parameter sizes.
Key Highlights:
• Supports 55 languages with high-quality translation across high-, mid-, and low-resource languages
• Exceptional efficiency: 12B model outperforms 27B baseline on WMT24++ benchmark
• Built using two-stage fine-tuning process distilling knowledge from Gemini models
• Retains strong multimodal capabilities (can translate text within images)
• Trained on nearly 500 additional language pairs for research adaptation
• Designed for diverse deployment environments from mobile to cloud
The models achieve state-of-the-art performance while maintaining exceptional efficiency, making high-quality translation accessible across different devices and use cases.
https://huggingface.co/collections/google/translategemma
Sri-Vigneshwar-DJ
posted
an
update
22 days ago
Post
307
Performance Marketing meets "Thinking Mode" 🧠
I’m excited to release hawky-ai-Qwen3-0.6B-Marketing-MoT, a specialized SLM designed for deep strategic reasoning in performance marketing.
While small at 0.6B parameters, this model punches way above its weight class by utilizing a Mixture of Thoughts (MoT) framework. It doesn't just give you an answer; it thinks through the logic of Meta Ads scaling, GA4 attribution, and unit economics before providing a strategic recommendation.
Key Features:
Thinking-First: Trained on 1,500+ critical thinking scenarios.
MoT Framework: 5 distinct reasoning styles (Linear, Exploratory, Critical, Deconstructive, Analogical).
SLM Speed: Perfect for low-latency, high-precision marketing audits.
Check it out on Hugging Face: 🔗 Sri-Vigneshwar-DJ/hawky-ai-Qwen3-0.6B-Marketing-MoT
I’m excited to release hawky-ai-Qwen3-0.6B-Marketing-MoT, a specialized SLM designed for deep strategic reasoning in performance marketing.
While small at 0.6B parameters, this model punches way above its weight class by utilizing a Mixture of Thoughts (MoT) framework. It doesn't just give you an answer; it thinks through the logic of Meta Ads scaling, GA4 attribution, and unit economics before providing a strategic recommendation.
Key Features:
Thinking-First: Trained on 1,500+ critical thinking scenarios.
MoT Framework: 5 distinct reasoning styles (Linear, Exploratory, Critical, Deconstructive, Analogical).
SLM Speed: Perfect for low-latency, high-precision marketing audits.
Check it out on Hugging Face: 🔗 Sri-Vigneshwar-DJ/hawky-ai-Qwen3-0.6B-Marketing-MoT
Post
3052
The new DeepSeek Engram paper is super fun! It also integrates mHC, and I suspect they're probably releasing all these papers to make the V4 report of reasonable length😄
Here's a nice short summary from Gemini
Here's a nice short summary from Gemini
prithivMLmods
posted
an
update
28 days ago
Post
5553
LTX-2 Camera-Control LoRA demo with dolly-in/out and dolly-left/right is now available on Hugging Face, paired with ltx-2-19b-distilled-lora for fast inference. It also includes dynamic GPU duration adjustments for long video generations. Click the related Space links below.
🤗Try it now on : prithivMLmods/LTX-2-LoRAs-Camera-Control-Dolly
⭐Github: https://github.com/PRITHIVSAKTHIUR/LTX-2-LoRAs-Camera-Control-Dolly
🕹️Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
To learn more, visit the app page or the respective model pages.
🤗Try it now on : prithivMLmods/LTX-2-LoRAs-Camera-Control-Dolly
⭐Github: https://github.com/PRITHIVSAKTHIUR/LTX-2-LoRAs-Camera-Control-Dolly
🕹️Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
To learn more, visit the app page or the respective model pages.
-
- 2 replies
Sri-Vigneshwar-DJ
posted
an
update
28 days ago
Post
2182
Introducing Hawky-AI H1 4B PM: The First Open-Source LLM for Performance Marketing 🎯
Hey HF Community! 👋
Just released the first LLM fine-tuned specifically for Performance Marketing.
What is it?
Gemma 3 4B distilled from Claude Opus 4.5 with expert-level marketing knowledge.
Covers:
📱 Meta Ads (campaign structure, bidding, scaling, creative fatigue)
🔍 Google Ads (Quality Score, Performance Max, lead gen)
📊 Measurement (ROAS vs MER, incrementality, LTV:CAC)
🎨 Creative Strategy (hook rates, A/B testing, funnel creative)
Why we built it:
Generic LLMs say "optimize your targeting" — not helpful. This model gives specific frameworks like "frequency at 4.5 + CTR drop = creative fatigue, here's the fix..."
Technical:
Base: Gemma 3 4B
Method: QLoRA (r=64)
Teacher: Claude Opus 4.5
🔗 Model: Sri-Vigneshwar-DJ/hawky-ai-H1-4b-PM
Built by Hawky.ai
Try it and let us know what you think! 🚀
Hey HF Community! 👋
Just released the first LLM fine-tuned specifically for Performance Marketing.
What is it?
Gemma 3 4B distilled from Claude Opus 4.5 with expert-level marketing knowledge.
Covers:
📱 Meta Ads (campaign structure, bidding, scaling, creative fatigue)
🔍 Google Ads (Quality Score, Performance Max, lead gen)
📊 Measurement (ROAS vs MER, incrementality, LTV:CAC)
🎨 Creative Strategy (hook rates, A/B testing, funnel creative)
Why we built it:
Generic LLMs say "optimize your targeting" — not helpful. This model gives specific frameworks like "frequency at 4.5 + CTR drop = creative fatigue, here's the fix..."
Technical:
Base: Gemma 3 4B
Method: QLoRA (r=64)
Teacher: Claude Opus 4.5
🔗 Model: Sri-Vigneshwar-DJ/hawky-ai-H1-4b-PM
Built by Hawky.ai
Try it and let us know what you think! 🚀