Classroom-workshop (Workshop June 13 Classroom)

julien-c

posted an update 15 days ago

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After some heated discussion 🔥, we clarify our intent re. storage limits on the Hub

TL;DR:
- public storage is free, and (unless blatant abuse) unlimited. We do ask that you consider upgrading to PRO and/or Enterprise Hub if possible
- private storage is paid above a significant free tier (1TB if you have a paid account, 100GB otherwise)

docs: https://huggingface.co./docs/hub/storage-limits

We optimize our infrastructure continuously to scale our storage for the coming years of growth in Machine learning, to the benefit of the community 🔥

cc: @reach-vb @pierric @victor and the HF team

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julien-c

posted an update 26 days ago

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wow 😮

INTELLECT-1 is the first collaboratively trained 10 billion parameter language model trained from scratch on 1 trillion tokens of English text and code.

PrimeIntellect/INTELLECT-1-Instruct

awacke1

posted an update about 1 month ago

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🕊️Hope🕊️ and ⚖️Justice⚖️ AI
🚲 Stolen bike in Denver FOUND - Sometimes hope & justice DO prevail.

🎬 So I Created an AI+Art+Music tribute:
-🧠 AI App that Evaluates GPT-4o vs Claude:
awacke1/RescuerOfStolenBikes
https://x.com/Aaron_Wacker/status/1857640877986033980?ref_src=twsrc%5Etfw%7Ctwcamp%5Etweetembed%7Ctwterm%5E1857640877986033980%7Ctwgr%5E203a5022b0eb4c41ee8c1dd9f158330216ac5be1%7Ctwcon%5Es1_c10&ref_url=https%3A%2F%2Fpublish.twitter.com%2F%3Furl%3Dhttps%3A%2F%2Ftwitter.com%2FAaron_Wacker%2Fstatus%2F1857640877986033980

<blockquote class="twitter-tweet"><p lang="en" dir="ltr">QT your 🕊️Hope🕊️ and ⚖️Justice⚖️ art🎨<br><br>🚲 Stolen bike in Denver FOUND! <br> - Sometimes hope &amp; justice DO prevail! <br><br>🎬 Created an AI+Art+Music tribute: <br> -🧠 AI App that Evaluates GPT-4o vs Claude: <a href="https://t.co/odrYdaeizZ">https://t.co/odrYdaeizZ</a><br> <a href="https://twitter.com/hashtag/GPT?src=hash&amp;ref_src=twsrc%5Etfw">#GPT</a> <a href="https://twitter.com/hashtag/Claude?src=hash&amp;ref_src=twsrc%5Etfw">#Claude</a> <a href="https://twitter.com/hashtag/Huggingface?src=hash&amp;ref_src=twsrc%5Etfw">#Huggingface</a> <a href="https://twitter.com/OpenAI?ref_src=twsrc%5Etfw">@OpenAI</a> <a href="https://twitter.com/AnthropicAI?ref_src=twsrc%5Etfw">@AnthropicAI</a> <a href="https://t.co/Q9wGNzLm5C">pic.twitter.com/Q9wGNzLm5C</a></p>&mdash; Aaron Wacker (@Aaron_Wacker) <a href="https://twitter.com/Aaron_Wacker/status/1857640877986033980?ref_src=twsrc%5Etfw">November 16, 2024</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

#GPT #Claude #Huggingface
@OpenAI
@AnthropicAI

awacke1

posted an update 2 months ago

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Since 2022 I have been trying to understand how to support advancement of the two best python patterns for AI development which are:
1. Streamlit
2. Gradio

The reason I chose them in this order was the fact that the streamlit library had the timing drop on gradio by being available with near perfection about a year or two before training data tap of GPT.

Nowadays its important that if you want current code to be right on generation it requires understanding of consistency in code method names so no manual intervention is required with each try.

With GPT and Claude being my top two for best AI pair programming models, I gravitate towards streamlit since aside from common repeat errors on cache and experimental functions circa 2022 were not solidified.
Its consistency therefore lacks human correction needs. Old dataset error situations are minimal.

Now, I seek to make it consistent on gradio side. Why? Gradio lapped streamlit for blocks paradigm and API for free which are I feel are amazing features which change software engineering forever.

For a few months I thought BigCode would become the new best model due to its training corpus datasets, yet I never felt it got to market as the next best AI coder model.

I am curious on Gradio's future and how. If the two main models (GPT and Claude) pick up the last few years, I could then code with AI without manual intervention. As it stands today Gradio is better if you could get the best coding models to not repeatedly confuse old syntax as current syntax yet we do live in an imperfect world!

Is anyone using an AI pair programming model that rocks with Gradio's latest syntax? I would like to code with a model that knows how to not miss the advancements and syntax changes that gradio has had in the past few years. Trying grok2 as well.

My IDE coding love is HF. Its hands down faster (100x) than other cloud paradigms. Any tips on models best for gradio coding I can use?

--Aaron

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awacke1

posted an update 2 months ago

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Today I was able to solve a very difficult coding session with GPT-4o which ended up solving integrations on a very large scale. So I decided to look a bit more into how its reasoners work. Below is a fun markdown emoji outline about what I learned today and what I'm pursuing.

Hope you enjoy! Cheers, Aaron.

Also here are my favorite last 4 spaces I am working on:
1. GPT4O: awacke1/GPT-4o-omni-text-audio-image-video
2. Claude:
awacke1/AnthropicClaude3.5Sonnet-ACW
3. MSGraph M365: awacke1/MSGraphAPI
4. Azure Cosmos DB: Now with Research AI! awacke1/AzureCosmosDBUI

# 🚀 OpenAI's O1 Models: A Quantum Leap in AI

## 1. 🤔 From 🦜 to 🧠: O1's Evolution

- **Thinking AI**: O1 ponders before replying; GPT models just predict. 💡

## 2. 📚 AI Memory: 💾 + 🧩 = 🧠

- **Embeddings & Tokens**: Words ➡️ vectors, building knowledge. 📖

## 3. 🔍 Swift Knowledge Retrieval

- **Vector Search & Indexing**: O1 finds info fast, citing reliable sources. 🔎📖

## 4. 🌳 Logic Trees with Mermaid Models

- **Flowchart Reasoning**: O1 structures thoughts like diagrams. 🎨🌐

## 5. 💻 Coding Mastery

- **Multilingual & Current**: Speaks many code languages, always up-to-date. 💻🔄

## 6. 🏆 Breaking Records

- **92.3% MMLU Score**: O1 outperforms humans, setting new AI standards. 🏅

## 7. 💡 Versatile Applications

- **Ultimate Assistant**: From fixing code to advancing research. 🛠️🔬

## 8. 🏁 Racing Toward AGI

- **OpenAI Leads**: O1 brings us closer to true AI intelligence. 🚀

## 9. 🤖 O1's Reasoning Pillars

- **🧠 Chain of Thought**: Step-by-step logic.
- **🎲 MCTS**: Simulates options, picks best path.
- **🔍 Reflection**: Self-improves autonomously.
- **🏋️‍♂️ Reinforcement Learning**: Gets smarter over time.

---

*Stay curious, keep coding!* 🚀

awacke1

posted an update 2 months ago

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I have finally completed a working full Azure and Microsoft MS Graph API implementation which can use all the interesting MS AI features in M365 products to manage CRUD patterns for the graph features across products.

This app shows initial implementation of security, authentication, scopes, and access to Outlook, Calendar, Tasks, Onedrive and other apps for CRUD pattern as AI agent service skills to integrate with your AI workflow.

Below are initial screens showing integration:

URL: awacke1/MSGraphAPI
Discussion: awacke1/MSGraphAPI#5

Best of AI on @Azure and @Microsoft on @HuggingFace :
https://huggingface.co./microsoft
https://www.microsoft.com/en-us/research/
---
Aaron

awacke1

posted an update 3 months ago

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Updated my 📺RTV🖼️ - Real Time Video AI app this morning.
URL: awacke1/stable-video-diffusion

It uses Stable Diffusion to dynamically create videos from images in input directory or uploaded using A10 GPU on Huggingface.

Samples below.

I may transition this to Zero GPU if I can. During Christmas when I revised this I had my highest billing from HF yet due to GPU usage. It is still the best turn key GPU out and Image2Video is a killer app. Thanks HF for the possibilities!

abidlabs

posted an update 3 months ago

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👋 Hi Gradio community,

I'm excited to share that Gradio 5 will launch in October with improvements across security, performance, SEO, design (see the screenshot for Gradio 4 vs. Gradio 5), and user experience, making Gradio a mature framework for web-based ML applications.

Gradio 5 is currently in beta, so if you'd like to try it out early, please refer to the instructions below:

---------- Installation -------------

Gradio 5 depends on Python 3.10 or higher, so if you are running Gradio locally, please ensure that you have Python 3.10 or higher, or download it here: https://www.python.org/downloads/

* Locally: If you are running gradio locally, simply install the release candidate with pip install gradio --pre
* Spaces: If you would like to update an existing gradio Space to use Gradio 5, you can simply update the sdk_version to be 5.0.0b3 in the README.md file on Spaces.

In most cases, that’s all you have to do to run Gradio 5.0. If you start your Gradio application, you should see your Gradio app running, with a fresh new UI.

-----------------------------

Fore more information, please see: https://github.com/gradio-app/gradio/issues/9463

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awacke1

posted an update 3 months ago

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My earliest / most popular AI example of using @pytorch for art has been updated with AI Pair Programming (AIPP) to use resolution of original inputs with @gradio and @AnthropicAI

For anyone learning AI model development - this is a great starter!

awacke1/Image-to-Line-Drawings

awacke1

posted an update 4 months ago

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590

I am integrating Azure Cosmos DB, the database system that backs GPT conversations into my workflow, and experimenting with new patterns to accelerate dataset evolution for evaluation and training of AI.

While initially using it for research prompts and research outputs using my GPT-4o client here which can interface and search ArXiv, I am excited to try out some new features specifically for AI at scale. Research on memory augmentation is shown. awacke1/GPT-4o-omni-text-audio-image-video

awacke1/AzureCosmosDBUI

awacke1

posted an update 5 months ago

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I just launched an exciting new multiplayer app powered by GPT-4o, enabling collaborative AI-driven queries in a single shared session!

### 🔗 Try It Out! 👉 Check out the GPT-4o Multiplayer App
Experience the future of collaborative AI by visiting our space on Hugging Face: awacke1/ChatStreamlitMultiplayer

🎉 This innovative tool lets you and your team reason over:

###📝 Text
###🖼️ Image
###🎵 Audio
###🎥 Video

## 🔍 Key Features

### Shared Contributions
Collaborate in real-time, seeing each other's inputs and contributions.
Enhances teamwork and fosters a collective approach to problem-solving.

### Diverse Media Integration
Seamlessly analyze and reason with text, images, audio, and video.
Breakthrough capabilities in handling complex media types, including air traffic control images and audio.

## 🛠️ Real-World Testing
This morning, we tested the app using images and audio from air traffic control—a challenge that was nearly impossible to handle with ease just a few years ago. 🚁💬

🌱 The Future of AI Collaboration
We believe AI Pair Programming is evolving into a new era of intelligence through shared contributions and teamwork. As we continue to develop, this app will enable groups to:

Generate detailed text responses 📝
Collaborate on code responses 💻
Develop new AI programs together 🤖

awacke1

posted an update 6 months ago

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✨🚀 Claude Sonnet 3.5 API. It's already weaving digital magic!
🧠💻 Try it at my space: 🔗 awacke1/AnthropicClaude3.5Sonnet-ACW

Kudos to @AnthropicAI for this elegant API! 👏 #AI #CodeMagic #AnthropicAI Thanks Huggingface for hosting the best hub in the world for AI development!

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abidlabs

posted an update 7 months ago

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𝗣𝗿𝗼𝘁𝗼𝘁𝘆𝗽𝗶𝗻𝗴 holds an important place in machine learning. But it has traditionally been quite difficult to go from prototype code to production-ready APIs

We're working on making that a lot easier with 𝗚𝗿𝗮𝗱𝗶𝗼 and will unveil something new on June 6th: https://www.youtube.com/watch?v=44vi31hehw4&ab_channel=HuggingFace

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julien-c

posted an update 7 months ago

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Hey it was good meeting you yesterday @MaziyarPanahi 🔥

thanks @mishig for setting this up

Let's make the Hub as useful as possible for the community ❤️

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awacke1

posted an update 8 months ago

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I just completed getting all four aspects of the new OpenAI GPT-4-o Omni model to process Text, Image, Audio, and Video.

Check it out and let me know what you think!

Space: awacke1/GPT-4o-omni-text-audio-image-video

Discussion: awacke1/GPT-4o-omni-text-audio-image-video

Test Runs for All Four Modalities: awacke1/GPT-4o-omni-text-audio-image-video#1

--Aaron - https://huggingface.co./awacke1

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nateraw

posted an update 8 months ago

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I just shared a blogpost on https://nateraw.com explaining the motivation + process of training nateraw/musicgen-songstarter-v0.2 - including training details, WandB logs, hparams, and notes on previous experiments.

Check it out here ⤵️
https://nateraw.com/posts/training_musicgen_songstarter.html

:) still kinda a WIP so if there's anything else you want to see, let me know.

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abidlabs

posted an update 8 months ago

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Open Models vs. Closed APIs for Software Engineers
-----------------------------------------------------------------------

If you're an ML researcher / scientist, you probably don't need much convincing to use open models instead of closed APIs -- open models give you reproducibility and let you deeply investigate the model's behavior.

But what if you are a software engineer building products on top of LLMs? I'd argue that open models are a much better option even if you are using them as APIs. For at least 3 reasons:

1) The most obvious reason is reliability of your product. Relying on a closed API means that your product has a single point-of-failure. On the other hand, there are at least 7 different API providers that offer Llama3 70B already. As well as libraries that abstract on top of these API providers so that you can make a single request that goes to different API providers depending on availability / latency.

2) Another benefit is eventual consistency going local. If your product takes off, it will be more economical and lower latency to have a dedicated inference endpoint running on your VPC than to call external APIs. If you've started with an open-source model, you can always deploy the same model locally. You don't need to modify prompts or change any surrounding logic to get consistent behavior. Minimize your technical debt from the beginning.

3) Finally, open models give you much more flexibility. Even if you keep using APIs, you might want to tradeoff latency vs. cost, or use APIs that support batches of inputs, etc. Because different API providers have different infrastructure, you can use the API provider that makes the most sense for your product -- or you can even use multiple API providers for different users (free vs. paid) or different parts of your product (priority features vs. nice-to-haves)

nateraw

posted an update 8 months ago

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Turns out if you do a cute little hack, you can make nateraw/musicgen-songstarter-v0.2 work on vocal inputs. 👀

Now, you can hum an idea for a song and get a music sample generated with AI 🔥🔥

Give it a try: ➡️ nateraw/singing-songstarter ⬅️

It'll take your voice and try to autotune it (because let's be real, you're no michael jackson), then pass it along to the model to condition on the melody. It works surprisingly well!

Violette

posted an update 8 months ago

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🔥 Next Thursday 4/25 at 8am PT / 11am ET / 17h CET, join our live Hugging Cast to learn how to deploy open models on Google Cloud.

Register ➡️ https://streamyard.com/watch/xz2nxp85Pi6e

@philschmid , @tengomucho , @jeffboudier will show you brand new Hub integrations built with GCP
🔥 with HF Inference Endpoints
🌎 with Vertex and GKE
🚀 on TPU

julien-c

posted an update 9 months ago

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text-generation-inference (TGI) is now fully open-source again!

Along with text-embeddings-inference.

We just switched both of those repos' license back to Apache 2. 🔥

Workshop June 13 Classroom

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