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maalberย  new activity 8 days ago
blog-explorers/README:Question regarding main section articles
AdrianLepersย  new activity 11 days ago
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maalberย  new activity 11 days ago
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prithivMLmodsย 
posted an update about 18 hours ago
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183
Idol-Imagine-Fast is now available on Hugging Face Spaces! Idol is paired with Z-Image-Turbo for fast, creative image generation. ๐Ÿ“ฆ๐Ÿ”ฅ

Space: prithivMLmods/idol-imagine-fast

โŸข Generate faster image assets for 3D generation
โŸข Automatic background removal with BRIA-RMBG-2.0
โŸข One-click image-to-3D generation
โŸข The default image-to-3D workflow remains unchanged, providing multiple inference options (text-to-image โ†’ 3D and image-to-3D).

๐Ÿ“ฆ GitHub: https://github.com/PRITHIVSAKTHIUR/idol-imagine-fast
๐Ÿ“ฆ Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection

To learn more, visit the Space or the respective model pages.
javadtaghiaย 
posted an update 3 days ago
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98
Can a general-purpose LLM erase a concept from a diffusion model by editing its weights directly, with no gradients?

We tested it under a preregistered protocol. GPT-6 Astra got tool access to the weights of segmind/tiny-sd and had to remove Van Gogh's painting style. Every edit was a closed-form tensor operation in a sandbox that blocks all autograd paths.

Held-out test, confirmatory runs (paired, template-clustered 95% CIs):
โ€ข vs random search with the same edit space and the same feedback: โˆ’52.1 pts Van Gogh rate [โˆ’61.7, โˆ’42.3]
โ€ข vs UCE (closed-form erasure): โˆ’11.5 pts [โˆ’22.9, โˆ’0.9], with identical damage to neighbouring painters
โ€ข vs ESD (gradient fine-tuning): equal removal, +11.8 pts better neighbour preservation

Limits, stated up front: one model ร— one concept so far; no method (the agent included) removes the style when it is described without the artist's name; no recovery attacks yet.

Every run is public: hash-chained logs, budgets, the agent's full transcripts, per-prompt scores, checkpoints, the frozen protocol and costs.

Article: https://huggingface.co/blog/javadtaghia/an-llm-erases-a-concept-by-editing-diffusion-weigh
Data: javadtaghia/unlearning-via-weight-public
Code: javadtaghia/unlearning-via-weight-code
danielhanchenย 
posted an update 3 days ago
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5,453
Qwen3.8-Flash-Next GGUFs now run faster with less thinking and less token use.

Unsloth Dynamic V3.1 GGUFs bring thinking & token use to match 95% of full precision Qwen3.8-Flash.

Results: 50% fewer tokens + 15% higher accuracy vs same size quants.

GGUF: unsloth/Qwen3.8-Flash-Next-GGUF
Analysis/Guide: https://unsloth.ai/docs/models/qwen3.8-next
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javadtaghiaย 
posted an update 4 days ago
danielhanchenย 
posted an update 6 days ago
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Weโ€™re releasing new Qwen3.8-Flash-Next GGUFs with 15% higher accuracy.

Unsloth Dynamic V3.1 outperforms others by >15% on Terminal Bench, DeepSWE & more benchmarks (256K context).

Run on 32GB+ RAM setups.

GGUF: unsloth/Qwen3.8-Flash-Next-GGUF
Blog: https://unsloth.ai/docs/models/qwen3.8-next
prithivMLmodsย 
posted an update 8 days ago
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5,432
VIGOR (Vision Intelligence and Guardrail Oriented Reasoning) is now available on the Hugging Face Model Hub. It is a multimodal vision classification model based on Qwen3.5, designed for visual content-safety analysis and conservative classification, with a particular focus on identifying potentially sensitive content.

๐Ÿ“ฆ Models: 27B, 9B, 4B โ€”

prithivMLmods/VIGOR-27B,
prithivMLmods/VIGOR-flash,
prithivMLmods/VIGOR-mini

โ†—๏ธ Collection:
https://huggingface.co/collections/prithivMLmods/vigor

To learn more, visit the app page or the respective model pages.
maalberย 
in blog-explorers/README 8 days ago

Question regarding main section articles

2
#37 opened 11 days ago by
maalber
javadtaghiaย 
posted an update 10 days ago
danielhanchenย 
posted an update 11 days ago
AdrianLepersย 
in blog-explorers/README 11 days ago

Question regarding main section articles

2
#37 opened 11 days ago by
maalber
danielhanchenย 
posted an update 13 days ago
prithivMLmodsย 
posted an update 17 days ago
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1,018
Flux-3-Image-Klein-LoRAs-Fast is now live on Hugging Face Spaces.๐Ÿค—๐Ÿ”ฅ

Plug and play with any custom LoRAs based on flux-3-image-klein. 16-step distilled fast inference, with support for prompt upsampling. More LoRAs will be added in the coming days!

๐Ÿ”— Space: prithivMLmods/flux-3-image-klein-loras-fast

๐Ÿ”— Image Generation Apps Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection

๐Ÿ”— GitHub: https://github.com/PRITHIVSAKTHIUR/flux-3-image-klein-loras-fast

To learn more, visit the app page or the respective model pages.
javadtaghiaย 
posted an update 17 days ago
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1,106
Hugging face article: https://huggingface.co/blog/javadtaghia/atmem-2310-bounded-evidence-discovery-for-persiste

AtMem 2.3.10 is out; and our full DolphinBench result has more than doubled.

AtMem 2.3.9 passed 192 of 600 tasks (32%).

AtMem 2.3.10 passed 390 of 600 (65%). We doubled it.

What changed?
We focused on how an agent discovers and uses evidence.
AtMem combined lexical and semantic retrieval while keeping related passages together with their original source and provenance and more.

Where do we stand?
This is substantial progress, with a clear tradeoff: median recorded task latency increased from 31.87 to 85.78 seconds. More successful investigation currently takes more time.
The published Hermes/Luna/Mem0 reference scores 424/600 (70.7%).

What comes next?
We want to understand the remaining failures: was evidence missing, poorly ranked, packed incompletely, interpreted with the wrong temporal state, or used incorrectly during an action?
Evidence discovery remains opt-in.
Release: https://github.com/aetna000/atmem/releases/tag/v2.3.10
DolphinBench submission PR: https://github.com/mem0ai/dolphinbench/pull/10
Results and execution evidence: atmem/atmem-2.3.10b1-dolphinbench

PS: DolphinBench tests whether an agent can use a simulated userโ€™s history to complete actions in applications. Finding a relevant passage isnโ€™t enoughโ€”a task passes only when all its required checks pass.
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javadtaghiaย 
posted an update 21 days ago
danielhanchenย 
posted an update 22 days ago
javadtaghiaย 
posted an update 25 days ago
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143
It is not always positive results that worth noting.
I ran a long run of training to improve AtMem (agent memory) on storage path using Laya as a decision model. However, I found it did not give me any better result than original AtMem.
Indeed we can use laya on the retrieval path, we have used than by pluging Jev. So we kinda proved something that is still a gap in memory systems (improving storage) is not as easy as it sounds. Check details https://huggingface.co/blog/javadtaghia/we-fine-tuned-a-memory-classifier-for-our-agent-he
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lucifertrjย 
posted an update 29 days ago
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146
Two ideas from Andrej Karpathyโ€™s tips on making LLM output easier to digest went into my last video:

> I put ASD-STE100 in the script guidelines so the narration sounds less AI-written
> then turned my project into a launch video with the Brag skill in Claude Code. (with voice)

+ ASD-STE100 also works well for video scripts.

๐Ÿ”— Watch on how to build these launch videos with single prompt: https://www.youtube.com/watch?v=OBX3b71n5EE
javadtaghiaย 
posted an update about 1 month ago
javadtaghiaย 
posted an update about 1 month ago
danielhanchenย 
posted an update about 1 month ago
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5,184
You can now train your own Decision model like Jev locally!

We increased Qwen3.5 0.8Bโ€™s aggregate accuracy from 20.7% to 74.3% across 3 decision benchmarks - on just 4GB VRAM.

Turn any LLM like Qwen3.8, Gemma 4 into decision models with our open-source Unsloth repo.

GitHub: https://github.com/unslothai/unsloth
Guide: https://unsloth.ai/docs/basics/train-your-own-decision-model-with-unsloth
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