and it fails mostly at instruction following
Sk md saad amin
Reality123b
AI & ML interests
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Recent Activity
replied to
TravisMuhlestein's
post
about 1 hour ago
Agentic AI doesn’t fail because it lacks intelligence — it fails because it lacks context.
As agents become more autonomous, the real challenge shifts from generation to governance:
understanding when, why, and under what constraints an agent should act.
At GoDaddy, we’ve been treating context as a first-class primitive for agentic systems —
combining identity, intent, permissions, and environment so agents can operate responsibly in production.
Context is what turns automation into judgment.
Without it, autonomy becomes risk.
This post outlines how we’re thinking about the transition from task execution to context-aware agentic systems, and what that means for building AI that can be trusted at scale.
👉 How we build context for agentic AI:
https://www.godaddy.com/resources/news/how-godaddy-builds-context-for-agentic-ai
Curious how others here are modeling context, trust boundaries, and decision constraints in agentic architectures.
liked
a dataset
about 4 hours ago
Reality123b/factsasvideos
new activity
about 4 hours ago
DataMuncher-Labs/UltraMath-Reasoning-Small:Formatting
Organizations
replied to
TravisMuhlestein's
post
about 1 hour ago
replied to
Ujjwal-Tyagi's
post
5 days ago
Yes, the guardrails in OpenAI’s models are complete [bad] it literally doesn't respond to a harmless programming query and says that Clifford+T gate is "not universal quantum computing", yes it happened to me once and I was so annoyed.
reacted to
Ujjwal-Tyagi's
post with 👍
5 days ago
Post
2656
For more better details and analysis, you can read the article here: https://huggingface.co/blog/Ujjwal-Tyagi/steering-not-censoring, We are sleepwalking into a crisis. I am deeply concerned about AI model safety right now because, as the community rushes to roll out increasingly powerful open-source models, we are completely neglecting the most critical aspect: safety. It seems that nobody is seriously thinking about the potential consequences of unregulated model outputs or the necessity of robust guardrails. We are essentially planting the seeds for our own destruction if we prioritize raw performance over security.
This negligence is terrifyingly evident when you look at the current landscape. Take Qwen Image 2512, for example; while it delivers undeniably strong performance, it has incredibly weak guardrails that make it dangerous to deploy. In stark contrast, Z Image might not get as much hype for its power, but it has much better safety guardrails than Qwen Image 2512.
It is imperative that the open-source community and developers recognize that capability without responsibility is a liability. We must actively work on protecting these models from bad actors who seek to exploit them for malicious purposes, such as generating disinformation, creating non-consensual imagery, or automating cyberattacks. It is no longer enough to simply release a powerful model; we must build layers of defense that make it resistant to jailbreaking and adversarial attacks. Developers need to prioritize alignment and robust filtering techniques just as much as they prioritize benchmark scores. We cannot hand such potent tools to the world without ensuring they have the safety mechanisms to prevent them from being turned against us.
This negligence is terrifyingly evident when you look at the current landscape. Take Qwen Image 2512, for example; while it delivers undeniably strong performance, it has incredibly weak guardrails that make it dangerous to deploy. In stark contrast, Z Image might not get as much hype for its power, but it has much better safety guardrails than Qwen Image 2512.
It is imperative that the open-source community and developers recognize that capability without responsibility is a liability. We must actively work on protecting these models from bad actors who seek to exploit them for malicious purposes, such as generating disinformation, creating non-consensual imagery, or automating cyberattacks. It is no longer enough to simply release a powerful model; we must build layers of defense that make it resistant to jailbreaking and adversarial attacks. Developers need to prioritize alignment and robust filtering techniques just as much as they prioritize benchmark scores. We cannot hand such potent tools to the world without ensuring they have the safety mechanisms to prevent them from being turned against us.
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- 17 replies
reacted to
nroggendorff's
post with 😔
5 days ago
Post
2896
I am now being charged for paused and unstarted spaces out of the blue.
I think this is it, folks. o7
The unstarted spaces I can get behind. I would've appreciated a warning email first, but whatever. However, every time I restart the active usage goes up, despite all of my spaces being moved to CPU (free), and being paused.
I think this is it, folks. o7
The unstarted spaces I can get behind. I would've appreciated a warning email first, but whatever. However, every time I restart the active usage goes up, despite all of my spaces being moved to CPU (free), and being paused.
- 13 replies
posted
an
update
5 days ago
Post
1059
We (DataMuncher-Labs) just made a new dataset for inducing mathematical and analytical reasoning in LLMs.
DataMuncher-Labs/UltraMath-Reasoning-Small
DataMuncher-Labs/UltraMath-Reasoning-Small
- 1 reply
reacted to
JLouisBiz's
post with 👍
6 days ago
Post
1835
I’ve built two Firefox extensions for my personal workflow:
1. **Quick Edit in Emacs**
I manage over 3,500 web pages locally. With this extension, I can now click anywhere on a webpage and instantly jump into Emacs to edit the exact page (or annotate any other page I'm working on).
2. **Describe Images (and soon Videos) on the Web**
Using the right-click menu, I can generate descriptions for images I come across online. These descriptions are stored and reused for my own image collections or web pages. I’m planning to add the same functionality for videos soon.
What makes this possible is running LLMs locally on my own machine — I’ve been experimenting with models like **Mistral Vibe** and others. This lets me automate description generation and text processing entirely offline, keeping everything fast, private, and fully under my control.
1. **Quick Edit in Emacs**
I manage over 3,500 web pages locally. With this extension, I can now click anywhere on a webpage and instantly jump into Emacs to edit the exact page (or annotate any other page I'm working on).
2. **Describe Images (and soon Videos) on the Web**
Using the right-click menu, I can generate descriptions for images I come across online. These descriptions are stored and reused for my own image collections or web pages. I’m planning to add the same functionality for videos soon.
What makes this possible is running LLMs locally on my own machine — I’ve been experimenting with models like **Mistral Vibe** and others. This lets me automate description generation and text processing entirely offline, keeping everything fast, private, and fully under my control.
reacted to
AdinaY's
post with 👍
6 days ago
Post
1466
Wechat AI is shipping!
WeDLM 🔥 A new language model that generates tokens in parallel, making it faster than standard LLMs , with the same Transformer setup!
https://huggingface.co/collections/tencent/wedlm
✨ 7B/8B - Base & Instruct
✨ Apache 2.0
WeDLM 🔥 A new language model that generates tokens in parallel, making it faster than standard LLMs , with the same Transformer setup!
https://huggingface.co/collections/tencent/wedlm
✨ 7B/8B - Base & Instruct
✨ Apache 2.0
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- 4 replies
reacted to
unmodeled-tyler's
post with 🚀
6 days ago
Post
1385
Atom-80B is out!:
vanta-research/atom-80b
I'm excited to share the new Atom-80B from VANTA Research! A few days ago we released the largest model-to-date from our portfolio, which was Atom-27B.
We've quickly scaled up to the new Qwen3 Next 80B architecture, bringing our friendly, curious, and collaborative Atom persona to cutting edge lightweight, high parameter inference.
Atom is designed to work and think alongside you through curious exploration. Using Atom collaboratively in your work can help spark your own creativity or curiosity. Give it a try!
I'm excited to share the new Atom-80B from VANTA Research! A few days ago we released the largest model-to-date from our portfolio, which was Atom-27B.
We've quickly scaled up to the new Qwen3 Next 80B architecture, bringing our friendly, curious, and collaborative Atom persona to cutting edge lightweight, high parameter inference.
Atom is designed to work and think alongside you through curious exploration. Using Atom collaboratively in your work can help spark your own creativity or curiosity. Give it a try!
- 1 reply
replied to
their
post
6 days ago
Wait... 128 GIGABYTES OR RAM IN THE RAMPOCALYPSE?!!
reacted to
MaziyarPanahi's
post with 🚀❤️
7 days ago
Post
2643
🎉 OpenMed 2025 Year in Review: 6 Months of Open Medical AI
I'm thrilled to share what the OpenMed community has accomplished since our July 2025 launch!
📊 The Numbers
29,700,000 downloads Thank you! 🙏
- 481 total models (475 medical NER models + 6 fine-tuned LLMs)
- 475 medical NER models in [OpenMed](
OpenMed
) organization
- 6 fine-tuned LLMs in [openmed-community](
openmed-community
)
- 551,800 PyPI downloads of the [openmed package](https://pypi.org/project/openmed/)
- 707 followers on HuggingFace (you!)
- 97 GitHub stars on the [toolkit repo](https://github.com/maziyarpanahi/openmed)
🏆 Top Models by Downloads
1. [OpenMed-NER-PharmaDetect-SuperClinical-434M]( OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M) — 147,305 downloads
2. [OpenMed-NER-ChemicalDetect-ElectraMed-33M]( OpenMed/OpenMed-NER-ChemicalDetect-ElectraMed-33M) — 126,785 downloads
3. [OpenMed-NER-BloodCancerDetect-TinyMed-65M]( OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-65M) — 126,465 downloads
🔬 Model Categories
Our 481 models cover comprehensive medical domains:
- Disease Detection (~50 variants)
- Pharmaceutical Detection (~50 variants)
- Oncology Detection (~50 variants)
- Genomics/DNA Detection (~80 variants)
- Chemical Detection (~50 variants)
- Species/Organism Detection (~60 variants)
- Protein Detection (~50 variants)
- Pathology Detection (~50 variants)
- Blood Cancer Detection (~30 variants)
- Anatomy Detection (~40 variants)
- Zero-Shot NER (GLiNER-based)
OpenMed
OpenMed NER: Open-Source, Domain-Adapted State-of-the-Art Transformers for Biomedical NER Across 12 Public Datasets (2508.01630)
https://huggingface.co/collections/OpenMed/medical-and-clinical-ner
https://huggingface.co/collections/OpenMed/zeroshot-medical-and-clinical-ner
OpenMed/Medical-Reasoning-SFT-GPT-OSS-120B
I'm thrilled to share what the OpenMed community has accomplished since our July 2025 launch!
📊 The Numbers
29,700,000 downloads Thank you! 🙏
- 481 total models (475 medical NER models + 6 fine-tuned LLMs)
- 475 medical NER models in [OpenMed](
- 6 fine-tuned LLMs in [openmed-community](
- 551,800 PyPI downloads of the [openmed package](https://pypi.org/project/openmed/)
- 707 followers on HuggingFace (you!)
- 97 GitHub stars on the [toolkit repo](https://github.com/maziyarpanahi/openmed)
🏆 Top Models by Downloads
1. [OpenMed-NER-PharmaDetect-SuperClinical-434M]( OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M) — 147,305 downloads
2. [OpenMed-NER-ChemicalDetect-ElectraMed-33M]( OpenMed/OpenMed-NER-ChemicalDetect-ElectraMed-33M) — 126,785 downloads
3. [OpenMed-NER-BloodCancerDetect-TinyMed-65M]( OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-65M) — 126,465 downloads
🔬 Model Categories
Our 481 models cover comprehensive medical domains:
- Disease Detection (~50 variants)
- Pharmaceutical Detection (~50 variants)
- Oncology Detection (~50 variants)
- Genomics/DNA Detection (~80 variants)
- Chemical Detection (~50 variants)
- Species/Organism Detection (~60 variants)
- Protein Detection (~50 variants)
- Pathology Detection (~50 variants)
- Blood Cancer Detection (~30 variants)
- Anatomy Detection (~40 variants)
- Zero-Shot NER (GLiNER-based)
OpenMed NER: Open-Source, Domain-Adapted State-of-the-Art Transformers for Biomedical NER Across 12 Public Datasets (2508.01630)
https://huggingface.co/collections/OpenMed/medical-and-clinical-ner
https://huggingface.co/collections/OpenMed/zeroshot-medical-and-clinical-ner
OpenMed/Medical-Reasoning-SFT-GPT-OSS-120B
- 1 reply
posted
an
update
14 days ago
Post
152
Thread to talk about the RAM shortage.
Guys I have RAM.
Please don't ban be for this, I know this is not directly related to AI
Guys I have RAM.
Please don't ban be for this, I know this is not directly related to AI
reacted to
nroggendorff's
post with 🔥
3 months ago
Post
3717
Is it hot in here, or is it just me?
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-
- 5 replies
posted
an
update
3 months ago
Post
280
made a new blog about releasing my new AI (hope i dont get banned for making an article for my own model) https://huggingface.co/blog/Reality123b/introducing-xylaria-2-exempted
replied to
their
post
4 months ago
probably
replied to
nroggendorff's
post
4 months ago
you didnt
posted
an
update
4 months ago
Post
297
I have a question for huggingface spaces. what hardware is the free cpu?
And what is the performance for that?
And what is the performance for that?
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- 8 replies
umm one thing i think no one can beat is jensen's leather jacket
is it gonna be available to all free users? as i got access