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efe

efecelik

AI & ML interests

NLP, LLM

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posted an update 3 minutes ago

We Built a Music App with ACE-Step – Looking for Feedback Hey everyone, We've been building AceSteps – a platform where anyone can create music using the ACE-Step model (https://huggingface.co/ACE-Step/ACE-Step-v1-3.5B). You can mint your tracks as NFTs, tokenize them into 100,000 fractional shares, and trade them on Uniswap V4. When your song gets popular, token holders earn from ad revenue automatically. It's a Farcaster Mini-App on Base Network. But we want to make it better, and we'd love your input: What's the one feature that would make you actually use an AI music tool regularly? Andd any suggestions on how we can make this model better? Actually sharing here for this question. 🤗 Any feedback, ideas, or critiques are welcome. 🔗 https://docs.acesteps.com/ 🔗 https://docs.acesteps.com/pitch-deck.html 🔗 https://farcaster.xyz/?launchFrameUrl=https%3A%2F%2Fwww.acesteps.com%2F 🔗 https://www.acesteps.com

commented on a paper 1 day ago

LTX-2: Efficient Joint Audio-Visual Foundation Model

upvoted a paper 1 day ago

LTX-2: Efficient Joint Audio-Visual Foundation Model

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posted an update 3 minutes ago

Post

We Built a Music App with ACE-Step – Looking for Feedback

Hey everyone,

We've been building AceSteps – a platform where anyone can create music using the ACE-Step model ( ACE-Step/ACE-Step-v1-3.5B). You can mint your tracks as NFTs, tokenize them into 100,000 fractional shares, and trade them on Uniswap V4. When your song gets popular, token holders earn from ad revenue automatically. It's a Farcaster Mini-App on Base Network.

But we want to make it better, and we'd love your input:

What's the one feature that would make you actually use an AI music tool regularly?
Andd any suggestions on how we can make this model better? Actually sharing here for this question. 🤗

Any feedback, ideas, or critiques are welcome.
🔗 https://docs.acesteps.com/
🔗 https://docs.acesteps.com/pitch-deck.html
🔗 https://farcaster.xyz/?launchFrameUrl=https%3A%2F%2Fwww.acesteps.com%2F
🔗 https://www.acesteps.com

replied to their post 2 days ago

Thanks for the detailed feedback! You're right that v1 has its quirks and we've experienced the repetition issues too.

Great to hear v1.5 is coming soon. Actually we built a platform called AceSteps using this model(v1). You can create music, mint it as an NFT, tokenize it into tradeable shares, and earn from ad revenue. It's a Farcaster Mini-App on Base Network.

Planning to integrate v1.5 once it drops.

Didn't know they had a Discord server, thanks for the info.

posted an update 3 days ago

Post

2256

why ACE-Step model isn't popular that much? imo it makes really good music.
ACE-Step/ACE-Step-v1-3.5B

2 replies

replied to Kseniase's post 25 days ago

this is a very good study. it reminded me of a time a few years ago when i found things like "few shots" and similar things ridiculous; that was a big mistake.

reacted to Kseniase's post with ❤️ 25 days ago

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3696

From Prompt Engineering to Context Engineering: Main Design Patterns

Earlier on, we relied on clever prompt wording, but now structured, complete context matters more than just magic phrasing. The next year is going to be a year of context engineering which expands beyond prompt engineering. The two complement each other: prompt engineering shapes how we ask, while context engineering shapes what the model knows, sees, and can do.

To keep things clear, here are the main techniques and design patterns in both areas, with some useful resources for further exploration:

▪️ 9 Prompt Engineering Techniques (configuring input text)

1. Zero-shot prompting – giving a single instruction without examples. Relies entirely on pretrained knowledge.

2. Few-shot prompting – adding input–output examples to encourage model to show the desired behavior. ⟶ https://arxiv.org/abs/2005.14165

3. Role prompting – assigning a persona or role (e.g. "You are a senior researcher," "Say it as a specialist in healthcare") to shape style and reasoning. ⟶ https://arxiv.org/abs/2403.02756

4. Instruction-based prompting – explicit constraints or guidance, like "think step by step," "use bullet points," "answer in 10 words"

5. Chain-of-Thought (CoT) – encouraging intermediate reasoning traces to improve multi-step reasoning. It can be explicit ("let’s think step by step"), or implicit (demonstrated via examples). ⟶ https://arxiv.org/abs/2201.11903

6. Tree-of-Thought (ToT) – the model explores multiple reasoning paths in parallel, like branches of a tree, instead of following a single chain of thought. ⟶ https://arxiv.org/pdf/2203.11171

7. Reasoning–action prompting (ReAct-style) – prompting the model to interleave reasoning steps with explicit actions and observations. It defines action slots and lets the model generate a sequence of "Thought → Action → Observation" steps. ⟶ https://arxiv.org/abs/2210.03629

Read further ⬇️
Also subscribe to Turing Post: https://www.turingpost.com/subscribe

3 replies

replied to KingNish's post 3 months ago

biggest gap in open source datasets is high quality, diverse data for ai, especially in scientific reasoning, multilingual, and multimodal domains

replied to Kseniase's post 3 months ago

open interpreter's my fave 'cause it runs locally, no cloud, and speeds up coding from the terminal

reacted to prithivMLmods's post with 😎 12 months ago

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5201

Deepswipe by
.
.
.
. Deepseek🐬🗿

Everything is now in recovery. 📉📈

4 replies

reacted to Csplk's post with ➕ over 1 year ago

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2943

# Offensive Security Reconnaissance Continued with Public Facing Industrial Control System HMIs using Moondream

Building on my previous experiments with Moondream for physical security reconnaissance planning automation (https://huggingface.co/posts/Csplk/926337297827024), I've now turned my attention to exploring the potential of this powerful image-text-text model for offensive security reconnaissance in the realm of Industrial Control Systems (ICS).
ICS HMIs (Human-Machine Interfaces) are increasingly exposed to the public internet, often without adequate security measures in place. This presents a tantalizing opportunity for malicious actors to exploit vulnerabilities and gain unauthorized access to critical infrastructure.

Using Moondream with batch processing ( Csplk/moondream2-batch-processing), I've been experimenting with analyzing public facing ICS ( Csplk/ICS_UIs) HMI ( Csplk/HMI) screenshots from shodan to identify types of exposed ICS system HMIs, how they are operated and how malicious actors with access to these systems could cause damage to physical infrastructure. Feeding images of HMIs and pre-defined text prompts to Moondream batch processing successfully (unconfirmed accuracy levels) extracted information about the underlying systems, including

1. **System type**
2. **Possible Operation Details**
3. **Malicious Actor Outcomes**

Next steps:
* I have a longer and more in depth blog write up in the works that will cover the previous and this post's approaches for experiments for sharing via HF community blog posts soon.
* I plan to continue refining my Moondream-based tool to improve its accuracy and effectiveness in processing public facing ICS HMIs.
* As mentioned before, offensive security with moondream focused HF Space once its fleshed out.

Thanks again to @vikhyatk for the incredible Moondream model. vikhyatk/moondream2

reacted to ezgikorkmaz's post with 👀 over 1 year ago

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1275

If you are interested in deep reinforcement learning, find my recent survey below:

A Survey Analyzing Generalization in Deep Reinforcement Learning
Paper: https://arxiv.org/pdf/2401.02349
GitHub: https://github.com/EzgiKorkmaz/generalization-reinforcement-learning

reacted to mmhamdy's post with ❤️ over 1 year ago

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3681

🚀 Introducing The Open Language Models List

This is a work-in-progress list of open language models with permissive licenses such as MIT, Apache 2.0, or other similar licenses.

The list is not limited to only autoregressive models or even only transformers models, and it includes many SSMs, and SSM-Transformers hybrids.

🤗 Contributions, corrections, and feedback are very welcome!

The Open Language Models List: https://github.com/mmhamdy/open-language-models

2 replies

reacted to fdaudens's post with ❤️ over 1 year ago

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1982

📫 AI in the news today: Struggling AI startups, Figure 0 robot, chipmakers

- OpenAI Co-Founders Schulman and Brockman Step Back
https://finance.yahoo.com/news/openai-co-founders-schulman-brockman-010542796.html

- Struggling AI Startups Look for a Bailout from Big Tech
"More exits—either pseudo-acquisitions or real ones—are coming, investors say, as a bubble built by the excitement around generative AI is showing signs of peaking."
https://www.wsj.com/tech/ai/struggling-ai-startups-look-for-a-bailout-from-big-tech-3e635927?mod=rss_Technology

- Did Google Just Pay $2.5 Billion to Hire Character's CEO?
https://www.theinformation.com/articles/did-google-just-pay-2-5-billion-to-hire-characters-ceo

- Figure’s new humanoid robot leverages OpenAI for natural speech conversations
Figure has unveiled its latest humanoid robot, the Figure 02.
The most notable addition this time out arrives by way a longstanding partnership with OpenAI, which helped Figure raise a $675 million Series B back in February, valuing the South Bay firm at $2.6 billion.
https://techcrunch.com/2024/08/06/figures-new-humanoid-robot-leverages-openai-for-natural-speech-conversations/

- World’s Five Leading Chipmakers Have Now Promised U.S. Investment
The Biden administration award up to $450 million in grants to a South Korean chipmaker, SK Hynix, to help build its new chip facility in Indiana
The US now has commitments from all five of the world’s leading-edge semiconductor manufacturers to construct chip plants in theUS with financial assistance from the administration
https://www.nytimes.com/2024/08/06/business/economy/chipmakers-promise-investment.html

reacted to Artples's post with 🚀 over 1 year ago

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2644

Looking for a combination of speed and quality? Look no further! I've created a space that merges Open WebUI's excellent interface and features with the lightning-fast performance of the Groq API. Experience top-tier models in no time. Try it out for free here:
https://huggingface.co/spaces/L-AI/groq-chat

"A big thank you to Groq for providing their fantastic API at no cost!"

reacted to MonsterMMORPG's post with ❤️ over 1 year ago

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12751

Kling AI Video is FINALLY Public (All Countries), Free to Use and MIND BLOWING - Full Tutorial > https://youtu.be/zcpqAxYV1_w

You probably seen those mind blowing AI made videos. And the day has arrived. The famous Kling AI is now worldwide available for free. In this tutorial video I will show you how to register for free with just email to Kling AI and use its mind blowing text to video animation, image to video animation and text to image, and image to image capabilities. This video will show you non-cherry pick results so you will know the actual quality and capability of the model unlike those extremely cherry pick example demos. Still, #KlingAI is the only #AI model that competes with OpenAI's #SORA and it is real to use.

🔗 Kling AI Official Website ⤵️
▶️ https://www.klingai.com/

🔗 SECourses Discord Channel to Get Full Support ⤵️
▶️ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388

🔗 Our GitHub Repository ⤵️
▶️ https://github.com/FurkanGozukara/Stable-Diffusion

🔗 Our Reddit ⤵️
▶️ https://www.reddit.com/r/SECourses/

6 replies

reacted to 1aurent's post with 🔥 over 1 year ago

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2619

Hey everyone 🤗!
Check out this cool new space from Finegrain: finegrain/finegrain-object-eraser

Under the hoods, it's a pipeline of models (currently exposed via an API) that allows you to easily erase any object from your image just by naming it or selecting it! Not only will the object disappear, but so will its effects on the scene, like shadows and reflections. Built on top of Refiners, our micro-framework for simple foundation model adaptation (feel free to star it on GitHub if you like it: https://github.com/finegrain-ai/refiners)

2 replies

reacted to severo's post with ❤️ over 1 year ago

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[New tool] Follow interesting ML persons 👩‍🎨 👨‍🎤 👩‍🏫 with Followgraph

severo/followgraph

Please try it and tell me if it helped you discover high-quality content 👍 👎

I repurposed "Followgraph for Mastodon" (https://followgraph.vercel.app/).

My new follows: @TheBloke @mlabonne @teknium @KnutJaegersberg @SkalskiP @AmelieSchreiber @lbourdois @ceyda @andrewyng @Pclanglais @karpathy

And you?

5 replies

reacted to as-cle-bert's post with ❤️ over 1 year ago

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5090

Hi HF Community!🤗

In the past days, OpenAI announced their search engine, SearchGPT: today, I'm glad to introduce you SearchPhi, an AI-powered and open-source web search tool that aims to reproduce similar features to SearchGPT, built upon microsoft/Phi-3-mini-4k-instruct, llama.cpp🦙 and Streamlit.
Although not as capable as SearchGPT, SearchPhi v0.0-beta.0 is a first step toward a fully functional and multimodal search engine :)
If you want to know more, head over to the GitHub repository (https://github.com/AstraBert/SearchPhi) and, to test it out, use this HF space: as-cle-bert/SearchPhi
Have fun!🐱

reacted to MonsterMMORPG's post with 👀 over 1 year ago

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1834

Just published Image Captioning Editor Gradio APP - Edit Your Captions Super Easy Including Batch Editing - For Windows, RunPod and Massed Compute. Developed by me. Have lots of amazing features that all you need. Let me know if missing any features.

Gradio is amazing to develop such amazing apps in short time. Used Claude 3.5 to develop it :)

Scripts are available here : https://www.patreon.com/posts/108992085

reacted to nevmenandr's post with ❤️ over 1 year ago

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2810

nevmenandr/w2v-chess

import gensim
from sklearn.decomposition import PCA
import matplotlib
import matplotlib.pyplot as plt

model = gensim.models.Word2Vec.load('white_moves.model')
dict_moves = model.wv.vocab
dict_moves_appr = {}
for k in dict_moves:
    if not k.startswith('->'):
        continue
    dict_moves_appr[k] = dict_moves[k]
X = model[model.wv.vocab]
pca = PCA(n_components=2)
result = pca.fit_transform(X)
fig, ax = plt.subplots()
ax.plot(Y[:, 0], Y[:, 1], 'o')
ax.set_title('White moves')
lab = list(dict_moves_appr)
for i, lb in enumerate(lab):
    plt.annotate(lb, xy=(Y[i, 0], Y[i, 1]))
plt.show()

biblically accurate angel

reacted to DrHouseFan-315's post with 🔥 over 1 year ago

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3224

Just made this!
https://github.com/takeraparterer/Charformer

20 replies

efe

AI & ML interests

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efecelik's activity