gg-hf-gg

community

Activity Feed

AI & ML interests

None defined yet.

Recent Activity

onath authored a paper 9 days ago

Can Vision-Language Models Evaluate Handwritten Math?

onath authored a paper 9 days ago

IndicDLP: A Foundational Dataset for Multi-Lingual and Multi-Domain Document Layout Parsing

ZachNagengast authored a paper about 1 month ago

WhisperKit: On-device Real-time ASR with Billion-Scale Transformers

View all activity

danielhanchen

posted an update 11 days ago

Post

3092

1-bit GLM-5.2 GGUF vs. Claude 4.8 Opus vs. GPT-5.5

We gave 3 models the same prompt and compared one-shot outputs.

The 1-bit GLM-5.2 GGUF ran locally on a Mac Studio M3 Ultra with 256GB RAM at ~21.6 tok/s.

Which output do you like best?
GGUF: unsloth/GLM-5.2-GGUF

3 replies

danielhanchen

posted an update 18 days ago

Post

4506

Google's new DiffusionGemma can now run at 2000+ tokens/sec! ⚡

We made local DiffusionGemma inference 1.8× faster.
Run it on 18GB RAM via Unsloth Studio.

GitHub: https://github.com/unslothai/unsloth
Guide: https://unsloth.ai/docs/models/diffusiongemma

4 replies

danielhanchen

posted an update 24 days ago

Post

1126

Google releases DiffusionGemma.✨
The new 26B-A4B diffusion text model runs locally on 18GB RAM.

Run with 4x faster text generation, thinking, image, video and 256K context. Run and train via Unsloth Studio.

GGUF: unsloth/diffusiongemma-26B-A4B-it-GGUF
Guide: https://unsloth.ai/docs/models/diffusiongemma

1 reply

danielhanchen

posted an update 26 days ago

Post

4232

Google releases Gemma 4 QAT. ✨
You can now run Gemma 4 at 3x less memory with near original performance.

QAT makes it possible to run Gemma 4 26B-A4B on 16GB RAM.

GGUFs: https://huggingface.co/collections/unsloth/gemma-4-qat
QAT Guide: https://unsloth.ai/docs/models/gemma-4/qat

1 reply

danielhanchen

posted an update about 1 month ago

Post

9257

Gemma 4 12B can now run locally on just 8GB RAM via Dynamic GGUFs.

Google's new model, Gemma 4 12B Unified supports image, audio and 256K context.
You can run and train the model via Unsloth Studio.

GGUF: unsloth/gemma-4-12b-it-GGUF
Guide: https://unsloth.ai/docs/models/gemma-4

5 replies

aalexandrov

authored a paper about 1 month ago

WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data

Paper • 2312.10188 • Published Dec 15, 2023

danielhanchen

posted an update about 1 month ago

Post

2806

Qwen3.6 MTP is here! Run locally on 20GB RAM. ⚡️

MTP enables Qwen3.6 to generate ~1.4–2.2× faster with no accuracy change.

Qwen3.6-27B: unsloth/Qwen3.6-27B-MTP-GGUF
Qwen3.6-35B-A3B: unsloth/Qwen3.6-35B-A3B-MTP-GGUF
Guide: https://unsloth.ai/docs/models/qwen3.6#mtp-guide

2 replies

danielhanchen

posted an update about 2 months ago

Post

5963

We’re excited to announce that Unsloth has joined the PyTorch Ecosystem! 🔥🦥

Unsloth is an open-source project that makes training & running models more accurate and faster with less compute. Our mission is to make local AI accessible to everyone. Thanks to all of you for making this possible! 💕

Blog: https://unsloth.ai/blog/pytorch
GitHub: https://github.com/unslothai/unsloth

2 replies

danielhanchen

posted an update about 2 months ago

Post

7772

We collaborated with NVIDIA to teach you how we made LLM training ~25% faster! 🚀

Learn how 3 optimizations help your home GPU train models faster:
1. Packed-sequence metadata caching
2. Double-buffered checkpoint reloads
3. Faster MoE routing

Guide: https://unsloth.ai/blog/nvidia-collab
GitHub: https://github.com/unslothai/unsloth

danielhanchen

posted an update about 2 months ago

Post

8911

We made a guide on how to run open LLMs in Claude Code, Codex and OpenClaw.

Use Gemma 4 and Qwen3.6 GGUFs for local agentic coding on 24GB RAM

Run with self-healing tool calls, code execution, web search via the Unsloth API endpoint and llama.cpp

Guide: https://unsloth.ai/docs/basics/api

safikhan

authored 8 papers 2 months ago

FairI Tales: Evaluation of Fairness in Indian Contexts with a Focus on Bias and Stereotypes

Paper • 2506.23111 • Published Jun 29, 2025

IndicIFEval: A Benchmark for Verifiable Instruction-Following Evaluation in 14 Indic Languages

Paper • 2602.22125 • Published Feb 25

Seeing Isn't Believing: Uncovering Blind Spots in Evaluator Vision-Language Models

Paper • 2604.21523 • Published Apr 23 • 4

Preferences of a Voice-First Nation: Large-Scale Pairwise Evaluation and Preference Analysis for TTS in Indian Languages

Paper • 2604.21481 • Published Apr 23 • 3

safikhan

submitted 2 papers to Daily Papers 2 months ago

Preferences of a Voice-First Nation: Large-Scale Pairwise Evaluation and Preference Analysis for TTS in Indian Languages

Paper • 2604.21481 • Published Apr 23 • 3

Seeing Isn't Believing: Uncovering Blind Spots in Evaluator Vision-Language Models

Paper • 2604.21523 • Published Apr 23 • 4

AI & ML interests

Recent Activity

Team members 291

gg-hf-gg's activity