Cultivar: A Contrastive and Locale-Oriented Translation Benchmark for Investigating Contamination and Localisation Robustness
Paper β’ 2608.09766 β’ Published β’ 6
AI & ML interests
LLM, LORA, text generation, prompt-tuning
Recent Activity
pinzhenchenΒ
authored a
paper 3 days ago
pinzhenchenΒ
submitted a
paper to Daily Papers 3 days ago
prithivMLmodsΒ
posted an update 15 days ago
Post
4942
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.π€
β Image-to-3D-Video-Asset-Generator: prithivMLmods/Image-to-3D-Video-Asset-Generator
β collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations
β github: https://github.com/PRITHIVSAKTHIUR/Image-to-3D-Video-Asset-Generator
β€· To learn more, visit the app page or the respective model pages.
β Image-to-3D-Video-Asset-Generator: prithivMLmods/Image-to-3D-Video-Asset-Generator
β collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations
β github: https://github.com/PRITHIVSAKTHIUR/Image-to-3D-Video-Asset-Generator
β€· To learn more, visit the app page or the respective model pages.
pinzhenchenΒ
authored 6
papers about 2 months ago
CHARM: Calibrating Reward Models With Chatbot Arena Scores
Paper β’ 2504.10045 β’ Published β’ 1
XL-Instruct: Synthetic Data for Cross-Lingual Open-Ended Generation
Paper β’ 2503.22973 β’ Published
DocHPLT: A Massively Multilingual Document-Level Translation Dataset
Paper β’ 2508.13079 β’ Published β’ 1
MatheMagic: Generating Dynamic Mathematics Benchmarks Robust to Memorization
Paper β’ 2510.05962 β’ Published
HPLT 3.0: Very Large-Scale Multilingual Resources for LLM and MT. Mono- and Bi-lingual Data, Multilingual Evaluation, and Pre-Trained Models
Paper β’ 2511.01066 β’ Published β’ 3
Reinforcement Learning Elicits Contextual Learning of Unseen Language Translation
Paper β’ 2606.06428 β’ Published β’ 25
prithivMLmodsΒ
posted an update about 2 months ago
Post
7930
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.π
β wan2.2-i2v-fast : prithivMLmods/Wan2.2-Fast
β github: https://github.com/prithivsakthiur/wan2.2-i2v-fast
β collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
β€· To learn more, visit the app page or the respective model pages.
β wan2.2-i2v-fast : prithivMLmods/Wan2.2-Fast
β github: https://github.com/prithivsakthiur/wan2.2-i2v-fast
β collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
β€· To learn more, visit the app page or the respective model pages.
prithivMLmodsΒ
posted an update 2 months ago
Post
2279
Dropping the collection of Qwen 3.5/3.6 MTP GGUF quants. π€
π Collection 1: https://huggingface.co/collections/prithivMLmods/mtp-qwen-35-36-moe-stable
π Collection 2: https://huggingface.co/collections/prithivMLmods/mtp-qwen-35-36-stable
> To learn more, visit the respective model pages.
π Collection 1: https://huggingface.co/collections/prithivMLmods/mtp-qwen-35-36-moe-stable
π Collection 2: https://huggingface.co/collections/prithivMLmods/mtp-qwen-35-36-stable
> To learn more, visit the respective model pages.
prithivMLmodsΒ
posted an update 3 months ago
Post
6310
PiD β 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!
π€ Space: prithivMLmods/PiD-Image-Upscaler
π Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
π€ > To learn more, visit the app page or the respective model pages.
π€ Space: prithivMLmods/PiD-Image-Upscaler
π Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
π€ > To learn more, visit the app page or the respective model pages.
prithivMLmodsΒ
posted an update 3 months ago
Post
5630
I've made 8 Spaces in the Qwen-Image-Edit series, and out of them, 5 Spaces reached βSpace of the Weekβ! 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! π€β€οΈ
π Spaces: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
Cumulatively, the series has crossed 8.2 million+ ZeroGPU runs and nearly 4 million visitors overall.
Thanks for all the community support! π€β€οΈ
π Spaces: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
- 4 replies
Ujjwal-TyagiΒ
posted an update 3 months ago
Post
520
6 Open-Source Libraries to FineTune LLMs
1. Unsloth
GitHub: https://github.com/unslothai/unsloth
β Fastest way to fine-tune LLMs locally
β Optimized for low VRAM (even laptops)
β Plug-and-play with Hugging Face models
2. Axolotl
GitHub: https://github.com/OpenAccess-AI-Collective/axolotl
β Flexible LLM fine-tuning configs
β Supports LoRA, QLoRA, multi-GPU
β Great for custom training pipelines
3. TRL (Transformer Reinforcement Learning)
GitHub: https://github.com/huggingface/trl
β RLHF, DPO, PPO for LLM alignment
β Built on Hugging Face ecosystem
β Essential for post-training optimization
4. DeepSpeed
GitHub: https://github.com/microsoft/DeepSpeed
β Train massive models efficiently
β Memory + speed optimization
β Industry standard for scaling
5. LLaMA-Factory
GitHub: https://github.com/hiyouga/LLaMA-Factory
β All-in-one fine-tuning UI + CLI
β Supports multiple models (LLaMA, Qwen, etc.)
β Beginner-friendly + powerful
6. PEFT
GitHub: https://github.com/huggingface/peft
β Fine-tune with minimal compute
β LoRA, adapters, prefix tuning
β Best for cost-efficient training
1. Unsloth
GitHub: https://github.com/unslothai/unsloth
β Fastest way to fine-tune LLMs locally
β Optimized for low VRAM (even laptops)
β Plug-and-play with Hugging Face models
2. Axolotl
GitHub: https://github.com/OpenAccess-AI-Collective/axolotl
β Flexible LLM fine-tuning configs
β Supports LoRA, QLoRA, multi-GPU
β Great for custom training pipelines
3. TRL (Transformer Reinforcement Learning)
GitHub: https://github.com/huggingface/trl
β RLHF, DPO, PPO for LLM alignment
β Built on Hugging Face ecosystem
β Essential for post-training optimization
4. DeepSpeed
GitHub: https://github.com/microsoft/DeepSpeed
β Train massive models efficiently
β Memory + speed optimization
β Industry standard for scaling
5. LLaMA-Factory
GitHub: https://github.com/hiyouga/LLaMA-Factory
β All-in-one fine-tuning UI + CLI
β Supports multiple models (LLaMA, Qwen, etc.)
β Beginner-friendly + powerful
6. PEFT
GitHub: https://github.com/huggingface/peft
β Fine-tune with minimal compute
β LoRA, adapters, prefix tuning
β Best for cost-efficient training
- 1 reply
prithivMLmodsΒ
posted an update 4 months ago
Post
5967
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.
π€ Demo: prithivMLmods/Multimodal-Edge-Node
π GitHub: https://github.com/PRITHIVSAKTHIUR/Multimodal-Edge-Node
β Multimodal Apps Collections: https://huggingface.co/collections/prithivMLmods/hall-of-multimodal-apps
π€ > To learn more, visit the app page or the respective model pages.
π€ Demo: prithivMLmods/Multimodal-Edge-Node
π GitHub: https://github.com/PRITHIVSAKTHIUR/Multimodal-Edge-Node
β Multimodal Apps Collections: https://huggingface.co/collections/prithivMLmods/hall-of-multimodal-apps
π€ > To learn more, visit the app page or the respective model pages.
Ujjwal-TyagiΒ
posted an update 4 months ago
Post
455
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.
prithivMLmodsΒ
posted an update 4 months ago
Post
1944
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. π
π Qwen3.6-MoE: https://huggingface.co/collections/prithivMLmods/qwen36-35b-a3b-compressions
π Qwen3.6-27B Compressions: https://huggingface.co/collections/prithivMLmods/qwen36-27b-compressions
π€ > To learn more, visit the app page or the respective model pages.
π Qwen3.6-MoE: https://huggingface.co/collections/prithivMLmods/qwen36-35b-a3b-compressions
π Qwen3.6-27B Compressions: https://huggingface.co/collections/prithivMLmods/qwen36-27b-compressions
π€ > To learn more, visit the app page or the respective model pages.
babytreeccΒ
authored a
paper 4 months ago
Ujjwal-TyagiΒ
posted an update 4 months ago
Post
3977
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
prithivMLmodsΒ
posted an update 4 months ago
Post
4245
HY-World-2.0 β A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds is now available on Spaces, and it works both as native Gradio components and in Gradio server mode.
> HY-World-2.0-Demo: prithivMLmods/HY-World-2.0-Demo
> HY-World-2.0 [Server Mode]: prithivMLmods/HY-World-2.0-Demo
> Featuring 3D reconstruction and Gaussian splats with the Rerun viewer, along with camera poses, depth maps, and surface normals.
> In Server Mode, Gradio is served via FastAPI, with FastAPI remaining the top-level server.
> Model: tencent/HY-World-2.0
> GitHub: https://github.com/PRITHIVSAKTHIUR/HY-World-2.0-Demo
π€To learn more, visit the app page or the respective model pages.
> HY-World-2.0-Demo: prithivMLmods/HY-World-2.0-Demo
> HY-World-2.0 [Server Mode]: prithivMLmods/HY-World-2.0-Demo
> Featuring 3D reconstruction and Gaussian splats with the Rerun viewer, along with camera poses, depth maps, and surface normals.
> In Server Mode, Gradio is served via FastAPI, with FastAPI remaining the top-level server.
> Model: tencent/HY-World-2.0
> GitHub: https://github.com/PRITHIVSAKTHIUR/HY-World-2.0-Demo
π€To learn more, visit the app page or the respective model pages.