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LLM, LORA, text generation, prompt-tuning

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pinzhenchen  authored a paper 9 days ago
Cultivar: A Contrastive and Locale-Oriented Translation Benchmark for Investigating Contamination and Localisation Robustness
pinzhenchen  submitted a paper 9 days ago
Cultivar: A Contrastive and Locale-Oriented Translation Benchmark for Investigating Contamination and Localisation Robustness
pinzhenchen  authored a paper 2 months ago
CHARM: Calibrating Reward Models With Chatbot Arena Scores
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prithivMLmods 
posted an update 2 days ago
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The Qwen3.8 27B demo for object grounding is now available on Hugging Face Spaces.

It features three tasks: Object Detection (Bounding Boxes), Point Localization (Keypoints), and Spatial Guidance (Path Mapping).

Try it now: prithivMLmods/Qwen3.8-27B-Object-Detection
pinzhenchen 
authored a paper 9 days ago
pinzhenchen 
submitted a paper to Daily Papers 9 days ago
prithivMLmods 
posted an update 21 days ago
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5494
Made a demo for Text/Image-to-3D Video and Image-to-3D Video asset generation using TRELLIS.2. It is paired with Z-Image-Turbo to accelerate the input image preprocessing pipeline, streamlining the Image-to-3D workflow. The generated GLB (GL Transmission Format) files are converted into MP4 (MPEG-4) videos, making them easy to preview and share. Try it now on Hugging Face Spaces.🤗

➠ Image-to-3D-Video-Asset-Generator: prithivMLmods/Image-to-3D-Video-Asset-Generator
➠ collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations
➠ github: https://github.com/PRITHIVSAKTHIUR/Image-to-3D-Video-Asset-Generator

⤷ To learn more, visit the app page or the respective model pages.
pinzhenchen 
authored 6 papers 2 months ago
prithivMLmods 
posted an update 2 months ago
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7945
Wan2.2-I2V-Fast with highly upscaled sequential frame sampling is now available as a Spaces demo, built using Wan2.2-I2V and FLUX.2-Klein. Try the demo using the links below.👇

➠ wan2.2-i2v-fast : prithivMLmods/Wan2.2-Fast
➠ github: https://github.com/prithivsakthiur/wan2.2-i2v-fast
➠ collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection

⤷ To learn more, visit the app page or the respective model pages.
prithivMLmods 
posted an update 3 months ago
prithivMLmods 
posted an update 3 months ago
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PiD — Pixel Diffusion Decoder Image Edit Upscale and Image Generation Upscale, an all-in-one demo, is now live on Spaces! Great improvements in realism-based image generation and editing are powered by FLUX.2-Klein, while image generation is paired with Z-Image, and upscaling is enabled by default!

🤗 Space: prithivMLmods/PiD-Image-Upscaler
🔗 Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection

🤗 > To learn more, visit the app page or the respective model pages.
prithivMLmods 
posted an update 3 months ago
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I've made 8 Spaces in the Qwen-Image-Edit series, and out of them, 5 Spaces reached “Space of the Week”! A few Spaces are still topping the list even after many months.

Cumulatively, the series has crossed 8.2 million+ ZeroGPU runs and nearly 4 million visitors overall.

Thanks for all the community support! 🤗❤️

🔗 Spaces: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
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Ujjwal-Tyagi 
posted an update 4 months ago
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6 Open-Source Libraries to FineTune LLMs
1. Unsloth
GitHub: https://github.com/unslothai/unsloth
→ Fastest way to fine-tune LLMs locally
→ Optimized for low VRAM (even laptops)
→ Plug-and-play with Hugging Face models

2. Axolotl
GitHub: https://github.com/OpenAccess-AI-Collective/axolotl
→ Flexible LLM fine-tuning configs
→ Supports LoRA, QLoRA, multi-GPU
→ Great for custom training pipelines

3. TRL (Transformer Reinforcement Learning)
GitHub: https://github.com/huggingface/trl
→ RLHF, DPO, PPO for LLM alignment
→ Built on Hugging Face ecosystem
→ Essential for post-training optimization

4. DeepSpeed
GitHub: https://github.com/microsoft/DeepSpeed
→ Train massive models efficiently
→ Memory + speed optimization
→ Industry standard for scaling

5. LLaMA-Factory
GitHub: https://github.com/hiyouga/LLaMA-Factory
→ All-in-one fine-tuning UI + CLI
→ Supports multiple models (LLaMA, Qwen, etc.)
→ Beginner-friendly + powerful

6. PEFT
GitHub: https://github.com/huggingface/peft
→ Fine-tune with minimal compute
→ LoRA, adapters, prefix tuning
→ Best for cost-efficient training
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prithivMLmods 
posted an update 4 months ago
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Multimodal-Edge Demo, a node-based inference canvas demo, is now live on Spaces. It features node-based Transformers for fast inference across 10+ edge-device multimodal models on the Hub, all within a single space. The series includes models from Qwen3.5, Qwen3-VL, Gemma 4, and the LFM 2.5 VL model series, with support for reasoning and grounding tasks.

🤗 Demo: prithivMLmods/Multimodal-Edge-Node
🔗 GitHub: https://github.com/PRITHIVSAKTHIUR/Multimodal-Edge-Node
✅ Multimodal Apps Collections: https://huggingface.co/collections/prithivMLmods/hall-of-multimodal-apps

🤗 > To learn more, visit the app page or the respective model pages.
Ujjwal-Tyagi 
posted an update 4 months ago
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This is the best set of AI and ML books and a full guide to learning machine learning from the ground up. This is my study material that I used, so I thought it would be helpful to share it with others. Like, share, and add it to your collection at Ujjwal-Tyagi/ai-ml-foundations-book-collection.
prithivMLmods 
posted an update 4 months ago
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Now, a collection of various compression schemes for Qwen3.6 and the abliterated version 1 of dense models is available on the Hub. Check it out via the links below. 👇

🔗 Qwen3.6-MoE: https://huggingface.co/collections/prithivMLmods/qwen36-35b-a3b-compressions
🔗 Qwen3.6-27B Compressions: https://huggingface.co/collections/prithivMLmods/qwen36-27b-compressions

🤗 > To learn more, visit the app page or the respective model pages.
babytreecc 
authored a paper 4 months ago
Ujjwal-Tyagi 
posted an update 4 months ago
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We are hiring at Shirova AI. We need AI researchers and engineers to work in our research lab. Shirova AI is a research lab in India, so we can help our researchers move to nearby workspaces or let them work from home without ever coming to the lab. We're building our founding team, so the pay will be good. You can learn, so don't hesitate to mail us at: careers@shirova.com