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longchen  authored a paper 9 days ago
DisPose: Disentangling Pose Guidance for Controllable Human Image Animation
longchen  authored a paper 3 months ago
LingoQA: Video Question Answering for Autonomous Driving
Yardenfren  updated a model 5 months ago
lora-library/B-LoRA-toy_storee
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Taylor658 
posted an update 23 days ago
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🌐 The Stanford Institute for Human-Centered AI (https://aiindex.stanford.edu/vibrancy/) has released its 2024 Global AI Vibrancy Tool, a way to explore and compare AI progress across 36 countries.

📊 It measures progress across the 8 broad pillars of R&D, Responsible AI, Economy, Education, Diversity, Policy and Governance, Public Opinion and Infrastructure. (Each of these pillars have a number of Sub Indices)

📈 As a whole it is not surprising that the USA was at the top in terms of overall score as of 2023 (AI investment activity is a large part of the economic pillar for example and that is a large part of the overall USA ranking) but drilling in to more STRATEGIC Macro pillars like Education, Infrastructure or R&D reveal interesting growth patterns in Asia (particularly China) and Western Europe that I suspect the 2024 metrics will bear out.

🤖 Hopefully the 2024 Global Vibrancy ranking will break out AI and ML verticals like Computer Vision or NLP and or the AI Agent space as that may also from a global macro level give indications of what is to come globally for AI in 2025.
victor 
posted an update 26 days ago
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1783
Qwen/QwQ-32B-Preview shows us the future (and it's going to be exciting)...

I tested it against some really challenging reasoning prompts and the results are amazing 🤯.

Check this dataset for the results: victor/qwq-misguided-attention
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Taylor658 
posted an update about 1 month ago
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🤖💻 Function Calling is a key component of Agent workflows. To call functions, an LLM needs a way to interact with other systems and run code. This usually means connecting it to a runtime environment that can handle function calls, data, and security.

Per the Berkeley Function-Calling Leaderboard there are only 2 fully open source models (The other 2 in the top 20 that are not closed source have cc-by-nc-4.0 licenses) out of the top 20 models that currently have function calling built in as of 17 Nov 2024.
https://gorilla.cs.berkeley.edu/leaderboard.html

The 2 Open Source Models out of the top 20 that currently support function calling are:

meetkai/functionary-medium-v3.1
Team-ACE/ToolACE-8B

This is a both a huge disadvantage AND an opportunity for the Open Source community as Enterprises, Small Business, Government Agencies etc. quickly adopt Agents and Agent workflows over the next few months. Open Source will have a lot of catching up to do as Enterprises will be hesitant to switch from the closed source models that they may initially build their Agent workflows on in the next few months to an open source alternative later.

Hopefully more open source models will support function calling in the near future.
victor 
posted an update about 1 month ago
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2255
Perfect example of why Qwen/Qwen2.5-Coder-32B-Instruct is insane?

Introducing: AI Video Composer 🔥
huggingface-projects/ai-video-composer

Drag and drop your assets (images/videos/audios) to create any video you want using natural language!

It works by asking the model to output a valid FFMPEG and this can be quite complex but most of the time Qwen2.5-Coder-32B gets it right (that thing is a beast). It's an update of an old project made with GPT4 and it was almost impossible to make it work with open models back then (~1.5 years ago), but not anymore, let's go open weights 🚀.
victor 
posted an update about 1 month ago
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Qwen2.5-72B is now the default HuggingChat model.
This model is so good that you must try it! I often get better results on rephrasing with it than Sonnet or GPT-4!!
Taylor658 
posted an update 2 months ago
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The Mystery Bot 🕵️‍♂️ saga I posted about from earlier this week has been solved...🤗

Cohere for AI has just announced its open source Aya Expanse multilingual model. The Initial release supports 23 languages with more on the way soon.🌌 🌍

You can also try Aya Expanse via SMS on your mobile phone using the global WhatsApp number or one of the initial set of country specific numbers listed below.⬇️

🌍WhatsApp - +14313028498
Germany - (+49) 1771786365
USA – +18332746219
United Kingdom — (+44) 7418373332
Canada – (+1) 2044107115
Netherlands – (+31) 97006520757
Brazil — (+55) 11950110169
Portugal – (+351) 923249773
Italy – (+39) 3399950813
Poland - (+48) 459050281
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Taylor658 
posted an update 2 months ago
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Spent the weekend testing out some prompts with 🕵️‍♂️Mystery Bot🕵️‍♂️ on my mobile... exciting things are coming soon for the following languages:

🌐Arabic, Chinese, Czech, Dutch, English French, German, Greek, Hebrew, Hindi, Indonesian, Italian, Japanese, Korean, Persian, Polish, Portuguese, Romanian, Russian, Spanish, Turkish, Ukrainian, and Vietnamese!🌐
victor 
posted an update 2 months ago
victor 
posted an update 3 months ago
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NEW - Inference Playground

Maybe like me you have always wanted a super easy way to compare llama3.2-1B vs. llama3.2-3B? or the same model with different temperatures?

Trying and comparing warm Inference API models has never been easier!
Just go to https://hf.co/playground, set your token and you're ready to go.
We'll keep improving, feedback welcome 😊
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Taylor658 
posted an update 3 months ago
Taylor658 
posted an update 4 months ago
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2350
💡Andrew Ng recently gave a strong defense of Open Source AI models and the need to slow down legislative efforts in the US and the EU to restrict innovation in Open Source AI at Stanford GSB.

🎥See video below
https://youtu.be/yzUdmwlh1sQ?si=bZc690p8iubolXm_
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victor 
posted an update 4 months ago
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🙋 Calling all Hugging Face users! We want to hear from YOU!

What feature or improvement would make the biggest impact on Hugging Face?

Whether it's the Hub, better documentation, new integrations, or something completely different – we're all ears!

Your feedback shapes the future of Hugging Face. Drop your ideas in the comments below! 👇
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victor 
posted an update 4 months ago
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How good are you at spotting AI-generated images?

Find out by playing Fake Insects 🐞 a Game where you need to identify which insects are fake (AI generated). Good luck & share your best score in the comments!

victor/fake-insects
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JoseRFJunior 
posted an update 5 months ago
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JoseRFJunior/TransNAR
https://github.com/JoseRFJuniorLLMs/TransNAR
https://arxiv.org/html/2406.09308v1
TransNAR hybrid architecture. Similar to Alayrac et al, we interleave existing Transformer layers with gated cross-attention layers which enable information to flow from the NAR to the Transformer. We generate queries from tokens while we obtain keys and values from nodes and edges of the graph. The node and edge embeddings are obtained by running the NAR on the graph version of the reasoning task to be solved. When experimenting with pre-trained Transformers, we initially close the cross-attention gate, in order to fully preserve the language model’s internal knowledge at the beginning of training.
victor 
posted an update 5 months ago
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Hugging Face famous organisations activity. Guess which one has the word "Open" in it 😂
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Yardenfren 
updated a model 5 months ago
Taylor658 
posted an update 6 months ago
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Researchers from Auburn University and the University of Alberta have explored the limitations of Vision Language Models (VLMs) in their recently published paper titled "Vision language models are blind." ( Vision language models are blind (2407.06581))

Key Findings:🔍
VLMs, including GPT-4o, Gemini-1.5 Pro, Claude-3 Sonnet, and Claude-3.5 Sonnet, struggle with basic visual tasks.
Tasks such as identifying where lines intersect or counting basic shapes are challenging for these models.
The authors noted, "The shockingly poor performance of four state-of-the-art VLMs suggests their vision is, at best, like of a person with myopia seeing fine details as blurry, and at worst, like an intelligent person that is blind making educated guesses"​(Vision Language Models Are Blind; 2024)​.

Human-like Myopia? 👓
VLMs may have a blind spot similar to human myopia.
This limitation makes it difficult for VLMs to perceive details.
Suggests a potential parallel between human and machine vision limitations.

Technical Details: 🔧
The researchers created a new benchmark called BlindTest.
BlindTest consists of simple visual tasks to evaluate VLMs low-level vision capabilities.
Four VLMs were assessed using BlindTest.
Many shortcomings were revealed in the models ability to process basic visual information.

Learn More: 🖼️
For a deeper dive into this research, check out the project page: https://vlmsareblind.github.io/
victor 
posted an update 6 months ago
Taylor658 
posted an update 6 months ago
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🌍 Cohere for AI has announced that this July and August, it is inviting researchers from around the world to join Expedition Aya, a global initiative focused on launching projects using multilingual tools like Aya 23 and Aya 101. 🌐

Participants can start by joining the Aya server, where all organization will take place. They can share ideas and connect with others on Discord and the signup sheet. Various events will be hosted to help people find potential team members. 🤝

To support the projects, Cohere API credits will be issued. 💰

Over the course of six weeks, weekly check-in calls are also planned to help teams stay on track and receive support with using Aya. 🖥️

The expedition will wrap up at the end of August with a closing event to showcase everyone’s work and plan next steps. Participants who complete the expedition will also receive some Expedition Aya swag. 🎉

Links:
Join the Aya Discord: https://discord.com/invite/q9QRYkjpwk
Visit the Expedition Aya Minisite: https://sites.google.com/cohere.com/expedition-aya/home
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Taylor658 
posted an update 6 months ago
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🔍 A recently published technical report introduces MINT-1T, a dataset that will considerably expand open-source multimodal data. It features one trillion text tokens and three billion images and is scheduled for release in July 2024.

Researcher Affiliation:

University of Washington
Salesforce Research
Stanford University
University of Texas at Austin
University of California, Berkeley

Paper:
MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens
https://arxiv.org/pdf/2406.11271v1.pdf

GitHub:
https://github.com/mlfoundations/MINT-1T

Highlights:

MINT-1T Dataset: Largest open-source multimodal interleaved dataset with 1 trillion text tokens & 3 billion images. 📊🖼️
Diverse Sources: Incorporates data from HTML, PDFs, and ArXiv documents. 📄📚
Open Source: Dataset and code will be released at https://github.com/mlfoundations/MINT-1T. 🌐🔓
Broader Domain Representation: Uses diverse data sources for balanced domain representation. 🌍📚
Performance in Multimodal Tasks: The dataset’s scale and diversity should enhance multimodal task performance. 🤖💡

Datasheet Information:

Motivation: Addresses the gap in large-scale open-source multimodal datasets. 🌐📊
Composition: 927.6 million documents, including HTML, PDF, and ArXiv sources. 📄📚
Collection Process: Gathered from CommonCrawl WARC and WAT dumps, with rigorous filtering. 🗂️🔍
Preprocessing/Cleaning: Removal of low-quality text, duplicates and anonymization of sensitive information. 🧹🔒
Ethical Considerations: Measures to ensure privacy and avoid bias. ⚖️🔏
Uses: Training multimodal models, generating interleaved image-text sequences, and building retrieval systems. 🤖📖