Hugging Face's logo
Activity Feed Request to join this org

AI & ML interests

Local LLMs

Recent Activity
parkneuralsΒ  authored a paper 28 days ago
KV Cache Recycling to Expand Usable Context Capacity in Low Parameter LLMs
guifre103Β  updated a model about 2 months ago
LocalLLaMA/GuifreAI
smcleodΒ  new activity 2 months ago
LocalLLaMA/GuifreAI:What's the organisation & project relating to (I'm a r/localllama mod)
View all activity
Aurelien-MorganΒ 
posted an update about 20 hours ago
view post
Post
83
@retrain-pipelines v0.2.0 is out !
I'm at Station F at My booth with GOSIM Paris 2026 today & tomorrow.
Come meet me for a live in-person demo and a chat !
Ujjwal-TyagiΒ 
posted an update 3 days ago
view post
Post
168
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 reply
Β·
Sri-Vigneshwar-DJΒ 
posted an update 4 days ago
view post
Post
78
![Feather DB LongMemEval Results]( Hawky-ai/longmemeval-results)

We ran Feather DB v0.8.0 on LongMemEval (ICLR 2025) β€” 500 questions across real multi-session conversations, up to 115K tokens each.

**Score: 0.693** Β· GPT-4o full-context baseline: 0.640
Full 500-question run with Gemini-Flash: **$2.40**

Per-axis breakdown:
β†’ Info-extraction: **0.942**
β†’ Knowledge-update: **0.714**
β†’ Multi-session: **0.606**
β†’ Temporal: **0.477** ← the hard one, Phase 9 addresses this

Architecture: Hybrid BM25+dense Β· adaptive temporal decay Β· embedded (no server) Β· p50 = 0.19ms Β· MIT

pip install feather-db

Raw results + audit JSONs: Hawky-ai/longmemeval-results
prithivMLmodsΒ 
posted an update 5 days ago
view post
Post
3633
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.

πŸ€— Demo: prithivMLmods/Multimodal-Edge-Node
πŸ”— GitHub: https://github.com/PRITHIVSAKTHIUR/Multimodal-Edge-Node
βœ… Multimodal Apps Collections: https://huggingface.co/collections/prithivMLmods/hall-of-multimodal-apps

πŸ€— > To learn more, visit the app page or the respective model pages.
Ujjwal-TyagiΒ 
posted an update 13 days ago
view post
Post
173
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 13 days ago
view post
Post
1832
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. πŸ‘‡

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

πŸ€— > To learn more, visit the app page or the respective model pages.
Ujjwal-TyagiΒ 
posted an update 15 days ago
view post
Post
3926
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 18 days ago
view post
Post
4153
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

πŸ€—To learn more, visit the app page or the respective model pages.
ParveshiiiiΒ 
posted an update 22 days ago
view post
Post
527
πŸš€ Sonic: A lightweight Python audio processing library with tempo matching, BPM detection, time-stretching, resampling & track blending β€” now with GPU (CUDA) acceleration for 10x speed!

Perfect for quick remixes, batch edits or syncing tracks.

πŸ‘‰ https://github.com/Parveshiiii/Sonic

#Python #AudioProcessing #OpenSource #PyTorch
Aurelien-MorganΒ 
posted an update 23 days ago
view post
Post
213
Launching a workweek of @retrain-pipelines wheels.

Day #1 : Compose
  • 4 replies
Β·
prithivMLmodsΒ 
posted an update 23 days ago
view post
Post
6187
A new comparator on Spaces showcases Standard FLUX.2 Decoder vs. FLUX.2 Small Decoder. The Small Decoder is ~1.4Γ— faster, uses ~1.4Γ— less VRAM, and maintains near-identical image quality. It has ~28M parameters with narrower channels [96, 192, 384, 384] vs. [128, 256, 512, 512], and the demo supports sequence generation by running both decoders simultaneously and comparing the results side by side.

πŸ€— Comparator: prithivMLmods/Flux.2-4B-Decoder-Comparator
πŸ”— FLUX.2-small-decoder: black-forest-labs/FLUX.2-small-decoder
πŸ”— GitHub: https://github.com/PRITHIVSAKTHIUR/Flux.2-4B-Encoder-Comparator
🚁 Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection

πŸ€— > App built on the Gradio SDK. To learn more, visit the app page or the respective model pages.
prithivMLmodsΒ 
posted an update 24 days ago
view post
Post
4223
Now, a collection of various compression schemes for Gemma 4 and the abliterated version 1 of dense models is available on the Hub. Check it out via the links below. πŸ‘‡

πŸ”—Gemma 4 Compression(s)- https://huggingface.co/collections/prithivMLmods/gemma-4-compressions
πŸ”—Gemma 4 Uncensored [MAX] + Compression(s) - [`Ξ² ]- https://huggingface.co/collections/prithivMLmods/gemma-4-uncensored-max-compressions
πŸ”—Gemma 4 Compression(s) - MoE- https://huggingface.co/collections/prithivMLmods/gemma-4-compressions-moe
πŸ”—Gemma-4 F32 GGUF- https://huggingface.co/collections/prithivMLmods/gemma-4-f32-gguf

πŸ€— > To learn more, visit the app page or the respective model pages.
prithivMLmodsΒ 
posted an update 27 days ago
view post
Post
2315
Now the demo for image detection based on SAM3 and Gemma-4 (*Filter) is available on Spaces, using full-fledged Transformers inference with multimodal reasoning for processed images. It also supports video segmentation (mask), video segmentation (annotation), and image click segmentation.

πŸ€— Demo Space: prithivMLmods/SAM3-Gemma4-CUDA
πŸ₯½ SAM3: facebook/sam3
πŸ”— gemma-4-E2B-it: google/gemma-4-E2B-it

To learn more, visit the app page or the respective model pages.
  • 1 reply
Β·
parkneuralsΒ 
authored a paper 28 days ago
ParveshiiiiΒ 
posted an update 29 days ago
view post
Post
1613
Excited to announce my latest open-source release on Hugging Face: Parveshiiii/breast-cancer-detector.

This model has been trained and validated on external datasets to support medical research workflows. It is designed to provide reproducible benchmarks and serve as a foundation for further exploration in healthcare AI.

Key highlights:
- Built for medical research and diagnostic study contexts
- Validated against external datasets for reliability
- Openly available to empower the community in building stronger, more effective solutions

This release is part of my ongoing effort to make impactful AI research accessible through **Modotte**. A detailed blog post explaining the methodology, dataset handling, and validation process will be published soon.

You can explore the model here: Parveshiiii/breast-cancer-detector

#AI #MedicalResearch #DeepLearning #Healthcare #OpenSource #HuggingFace

prithivMLmodsΒ 
posted an update about 1 month ago
view post
Post
4756
The demo for Image Detection (*Filter) based on SAM3 and Qwen-3.5 is now available on Hugging Face Spaces using Transformers inference, with multimodal reasoning for processed images, and it also supports video segmentation (mask), video segmentation (annotation), and image click segmentation.

πŸ€— Demo Space: prithivMLmods/SAM3-Plus-Qwen3.5
πŸ₯½ SAM3: facebook/sam3
πŸ”— Qwen-3.5: Qwen/Qwen3.5-2B

To learn more, visit the app page or the respective model pages.
  • 5 replies
Β·
MaziyarPanahiΒ 
posted an update about 1 month ago
view post
Post
2201
Training mRNA Language Models Across 25 Species for $165

We built an end-to-end protein AI pipeline covering structure prediction, sequence design, and codon optimization. After comparing multiple transformer architectures for codon-level language modeling, CodonRoBERTa-large-v2 emerged as the clear winner with a perplexity of 4.10 and a Spearman CAI correlation of 0.40, significantly outperforming ModernBERT. We then scaled to 25 species, trained 4 production models in 55 GPU-hours, and built a species-conditioned system that no other open-source project offers. Complete results, architectural decisions, and runnable code below.

https://huggingface.co/blog/OpenMed/training-mrna-models-25-species
OzTianluΒ 
posted an update about 1 month ago
view post
Post
1405
https://github.com/lizixi-0x2F/March
I just released March, an open-source high-performance KV cache sharing library for LLM inference that uses Trie-based prefix deduplication.
When you run LLM services, you often see thousands of requests sharing the same system prompt and conversation history. But traditional KV cache systems store each sequence separately β€” duplicating the exact same data over and over again. Pure waste.
March uses a Trie structure to automatically detect and reuse identical token prefixes. Instead of storing [system_prompt + history] 1000 times, it's stored once. Everyone shares it.
- 80-97% memory reduction in prefix-heavy workloads (tested on SmolLM2-135M with 500 multi-turn conversations)
- Zero-copy queries β€” returns direct pointers into the memory pool, no expensive memcpy on the hot path
- Predictable memory usage β€” fixed-size page pool with O(L) complexity
- Trade-off: slightly slower than dict O(1) lookup, but the memory savings are worth it in production
  • 1 reply
Β·
Ujjwal-TyagiΒ 
posted an update about 1 month ago
view post
Post
2815
I am sharing my study material for AI & ML, these books are really a "bible" and gives very strong foundation, I also have given guidance, introduction and my master notes in the dataset repo card! I hope you will find them helpful, if you have any queries, just start a discussion and I am always there to help you out!
Ujjwal-Tyagi/ai-ml-foundations-book-collection
  • 4 replies
Β·
prithivMLmodsΒ 
posted an update about 1 month ago
view post
Post
5311
Flux-Klein-KV-Edit-Consistency demo is now available on Spaces. It preserves character identity and delivers high-quality, realistic results after edits. No need for any special prompts, just upload the image, type your prompt, and get the resulting image blazing fast.

πŸ”₯ Demo Space: prithivMLmods/flux-klein-kv-edit-consistency
πŸ€— Model: black-forest-labs/FLUX.2-klein-9b-kv
πŸ€— Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
πŸ”— Gradio Server Mode: https://www.gradio.app/main/guides/server-mode

βž” Built with Headless Gradio, an alternative to using gr.Blocks for creating the frontend and triggering events, powered by FastAPI + Gradio. You can now design the frontend however you want, with continued support for APIs, MCP, and ZeroGPU.

βž” Gradio Server Mode is now available from gradio@v6.10.0.

To learn more, visit the app page or the respective model pages.