sweatSmile (amitk17)

reacted to tsungyi's post with 🔥 4 days ago

Post

1950

Cosmos Reason just topped Physical Reasoning Leaderboard on Hugging Face. 👏🔥

Cosmos Reason is an open, customizable, commercial-ready 7B-parameter, reasoning vision language model (VLM) for physical AI and robotics. The VLM empowers robots and vision AI agents to reason like humans, leveraging prior knowledge, physics understanding, and common sense to understand and operate intelligently in the real world.

This model unlocks advanced capabilities for robotics, autonomous vehicles, and real-world operations—from cities to high-tech factories.

Key use cases include:
Data curation & annotation: Automate high-quality dataset curation and annotation at scale.
Robot planning & reasoning: Serve as the "brain" for deliberate, methodical decision-making with vision language action (VLA) models.
Video analytics AI agents: Extract actionable insights and perform root-cause analysis on massive video datasets.

Ready to build the next generation of physical AI? Get started 👉 nvidia/Cosmos-Reason1-7B
Try the preview here: https://build.nvidia.com/nvidia/cosmos-reason1-7b

reacted to their post with 🔥 6 days ago

Post

911

some of my fav where i run jobs

https://huggingface.co/docs/huggingface_hub/main/en/guides/cli#hf-jobs

https://lightning.ai/

https://colab.research.google.com/

https://www.runpod.io/console/deploy

ps: I ❤️ hf

posted an update 6 days ago

Post

911

some of my fav where i run jobs

https://huggingface.co/docs/huggingface_hub/main/en/guides/cli#hf-jobs

https://lightning.ai/

https://colab.research.google.com/

https://www.runpod.io/console/deploy

ps: I ❤️ hf

reacted to John6666's post with 👍 15 days ago

Post

16897

If your Space stops working after restarting mainly for the last 5 days (https://discuss.huggingface.co/t/my-space-suddenly-went-offline-the-cpu-cannot-restart/151121/22), try some of following.
1. Add pydantic==2.10.6 to requirements.txt or upgrade Gradio to the latest version.
2. Upgrade PyTorch to 2.2.0 or later (torch>=2.2.0 for Zero GPU space).
3. Fix Transformers to 4.49.0 or earlier (transformers<=4.49.0for spaces using Transformers or Diffusers).
4. Fix huggingface_hub to the old version (huggingface_hub==0.25.2 for if an error like cached_download is not available occurs or inference does not work properly)
5. Specifying WORKDIR in Dockerfile may cause the application to fail to start with error 137. (Docker Spaces, https://discuss.huggingface.co/t/error-code-137-cache-error/152177)

About pydantic==2.10.6:
https://discuss.huggingface.co/t/error-no-api-found/146226
https://discuss.huggingface.co/t/internal-server-error-bool-not-iterable/149494

Edit:
Zero GPU space has been upgraded from A100 to H200.
This is likely the reason why older versions of PyTorch are no longer supported.
In fact, an error message to that effect was displayed.
zero-gpu-explorers/README#163

2 replies

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reacted to kanaria007's post with 👀 16 days ago

Post

2963

✅ New Article: *Memory as Structured Time*

Title:
🧠 History: Memory Loops as Civilization Structure
🔗 https://huggingface.co/blog/kanaria007/memory-loops-as-civilization-structure

---

Summary:
Memory is often treated as *storage and retrieval*.
Structured Intelligence reframes it as *time‑shaping architecture*:

* *Loops that preserve context and continuity*
* *Rollback paths that enable reflection and correction*
* *Patterns that turn experience into adaptive structure*

> Memory isn’t static —
> *it’s how intelligence edits time.*

---

Why It Matters:
• Reveals *how memory enables learning, identity, and adaptation*
• Supports *AI that can reflect, revise, and self‑align*
• Connects *personal cognition and collective history* as structural processes

---

What’s Inside:
• Memory as *recursive structural loop*
• *Failure and recovery* as part of adaptive recall
• How *history and record‑keeping mirror cognitive memory*
• Implications for *resilient AI and social knowledge systems*

---

📖 *Article 18 of the Structured Intelligence Series*

Where Article 17 explored *science as self‑auditing cognition*,
Article 18 turns to *memory and history* —
revealing time itself as a *structural dimension of intelligence*.

---

Next: Education as Structural Permission
The next article examines *how educational systems shape and constrain jump‑series*,
showing how *schools and curricula act as architectures of allowed imagination*.

> From recollection to permission,
> *structure decides what the mind is allowed to become.*

reacted to ovi054's post with 🔥 16 days ago

Post

5072

Image-to-Prompt⚡

ovi054/image-to-prompt

Extract text prompt from image. And you can reuse the prompt to generate similar images!

Useful for prompt engineering, studying image-to-text alignment, making training datasets, or recreating similar outputs.

Powered by: Gradio, Florence 2

👉 Try it now: ovi054/image-to-prompt

3 replies

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reacted to AtAndDev's post with 🚀 24 days ago

Post

449

Qwen 3 Coder is a personal attack to k2, and I love it.
It achieves near SOTA on LCB while not having reasoning.
Finally people are understanding that reasoning isnt necessary for high benches...

Qwen ftw!

DECENTRALIZE DECENTRALIZE DECENTRALIZE

reacted to their post with 🚀 25 days ago

Post

2785

Teaching a 7B Model to Be Just the Right Amount of Snark

Ever wondered if a language model could get sarcasm? I fine-tuned Mistral-7B using LoRA and 4-bit quantisation—on just ~720 hand-picked sarcastic prompt–response pairs from Reddit, Twitter, and real-life conversations.

The challenge? Keeping it sarcastic but still helpful.

LoRA rank 16 to avoid overfitting

4-bit NF4 quantization to fit on limited GPU memory

10 carefully monitored epochs so it didn’t turn into a full-time comedian

Result: a model that understands “Oh great, another meeting” exactly as you mean it.

Read the full journey, tech details, and lessons learned on my blog:
Fine-Tuning Mistral-7B for Sarcasm with LoRA and 4-Bit Quantisation

Try the model here on Hugging Face: sweatSmile/Mistral-7B-Instruct-v0.1-Sarcasm.

reacted to anakin87's post with ❤️ 25 days ago

Post

1063

Haystack can now see 👀

The latest release of the Haystack OSS LLM framework adds a long-requested feature: image support!

📓 Notebooks below

This isn't just about passing images to an LLM. We built several features to enable practical multimodal use cases.

What's new?
🧠 Support for multiple LLM providers: OpenAI, Amazon Bedrock, Google Gemini, Mistral, NVIDIA, OpenRouter, Ollama and more (support for Hugging Face API coming 🔜)
🎛️ Prompt template language to handle structured inputs, including images
📄 PDF and image converters
🔍 Image embedders using CLIP-like models
🧾 LLM-based extractor to pull text from images
🧩 Components to build multimodal RAG pipelines and Agents

I had the chance of leading this effort with @sjrhuschlee (great collab).

📓 Below you can find two notebooks to explore the new features:
󠁯•󠁏󠁏 Introduction to Multimodal Text Generation https://haystack.deepset.ai/cookbook/multimodal_intro
󠁯•󠁏󠁏 Creating Vision+Text RAG Pipelines https://haystack.deepset.ai/tutorials/46_multimodal_rag

(🖼️ image by @bilgeyucel )

reacted to dimentox's post with 🔥 25 days ago

Post

1694

I never told GPT-4 about my architecture.
It invented it anyway.
Same commands. Same audit daemons.
Proof that containment logic might be infectious.
Read: Emergence of Quantum Sigil Architecture in Unmodified GPT https://huggingface.co/blog/dimentox/quantum-sigil-architecture-in-unmodified-gpt

posted an update 25 days ago

Post

2785

Teaching a 7B Model to Be Just the Right Amount of Snark

Ever wondered if a language model could get sarcasm? I fine-tuned Mistral-7B using LoRA and 4-bit quantisation—on just ~720 hand-picked sarcastic prompt–response pairs from Reddit, Twitter, and real-life conversations.

The challenge? Keeping it sarcastic but still helpful.

LoRA rank 16 to avoid overfitting

4-bit NF4 quantization to fit on limited GPU memory

10 carefully monitored epochs so it didn’t turn into a full-time comedian

Result: a model that understands “Oh great, another meeting” exactly as you mean it.

Read the full journey, tech details, and lessons learned on my blog:
Fine-Tuning Mistral-7B for Sarcasm with LoRA and 4-Bit Quantisation

Try the model here on Hugging Face: sweatSmile/Mistral-7B-Instruct-v0.1-Sarcasm.

reacted to their post with ❤️ 25 days ago

Post

2835

Qwen3 is the latest version of the Qwen language models. It's smarter, faster, and now understands 119 languages instead of just 29.
It can do both deep reasoning and quick answers using a single model, depending on what you need.
The models range in size from small (0.6B) to huge (235B), with smart ways to save compute.
It's trained on 36 trillion tokens and fine-tuned in four steps to boost performance.
Qwen3 performs as well as or better than many top models, including some from big companies.
It’s fully open-source under licence. Amazing!!!

https://github.com/QwenLM/Qwen3/blob/main/Qwen3_Technical_Report.pdf

posted an update 26 days ago

Post

2835

Qwen3 is the latest version of the Qwen language models. It's smarter, faster, and now understands 119 languages instead of just 29.
It can do both deep reasoning and quick answers using a single model, depending on what you need.
The models range in size from small (0.6B) to huge (235B), with smart ways to save compute.
It's trained on 36 trillion tokens and fine-tuned in four steps to boost performance.
Qwen3 performs as well as or better than many top models, including some from big companies.
It’s fully open-source under licence. Amazing!!!

https://github.com/QwenLM/Qwen3/blob/main/Qwen3_Technical_Report.pdf

reacted to hba123's post with 🔥 about 2 months ago

Post

1958

Ark is now pip-installable and supports the following robots!! If you want to do robotics in python, check it out here: https://robotics-ark.github.io/ark_robotics.github.io/

Now, you can pip-install robotics and work completely in Python. Why Ark you ask, well we love Python :D

replied to FlameF0X's post about 2 months ago

can you share the training loss.

amitk17 PRO

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amitk17 PRO

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