Hugging Face

Hugging Face is a platform sharing tools, models, datasets, focused on democratizing AI. It is a sort of collaborative hub for an AI community, but it is also registered as a private company teaming up with, for instance, Meta to boost European startups in an "AI Accelerator Program". The company also collaborates with Amazon Web Services to allow users to deploy the trained and publicly available models in Hugging Face through Amazon SageMaker. Nasdaq Private Market lists a whole range of investors in Hugging Face (Amazon, Google, Intel, IBM, NVIDIA, etc.), and its estimated market value was $4.5 billion in 2023, which of course also reflects the high expertise the company has in managing models, hosting them, and making them available.

A diagram by the European Business review representing Hugging Face business model https://www.europeanbusinessreview.com/hugging-face-why-do-most-tech-companies-in-ai-collaborate-with-hugging-face/

What is Hugging Face?

Hugging Face is a platform sharing tools, models, datasets, focused on democratizing AI. It is a sort of collaborative hub for an AI community. It is not specifically targeted AI image creation, but generative AI more broadly. For instance, one might find a dataset for creating 2-D, cartoon-line video game characters.

Access to, and not least integration of models is a complicated issue that demands high technical expertise. More than anything, what Hugging Face offers is therefore an infrastructure.

I had used this same image set for some experimental tests on Stable Diffusion XL via LORA and Dreambooth training methods for some solid results post-training

Upload datasets - train models

.... training models at large scale

+ customisation for clients / manually racks of machines

Upload a dataset / accesss for others to download

But also to access models on HF

https://huggingface.co/datasets/mgane/2D_Video_Game_Cartoon_Character_Sprite-Sheets

"mgane/2D_Video_Game_Cartoon_Character_Sprite-Sheets" - a "76 cartoon art-style video game character spritesheets"

"All images editted using Tiled image editting software as most assets are typically downloaded individually and not in sequence. I compiled each animation sequence into one img to display animations frame-by-frame evenly distributed across some common animations seen in 2D video game art (Idle, Attack, Walk, Running, etc). I had used this same image set for some experimental tests on Stable Diffusion XL via LORA and Dreambooth training methods for some solid results post-training."

https://huggingface.co/datasets/mgane/2D_Video_Game_Cartoon_Character_Sprite-Sheets

but it is also registered as a private company teaming up with, for instance, Meta to boost European startups in an "AI Accelerator Program". The company also collaborates with Amazon Web Services to allow users to deploy the trained and publicly available models in Hugging Face through Amazon SageMaker. Nasdaq Private Market lists a whole range of investors in Hugging Face (Amazon, Google, Intel, IBM, NVIDIA, etc.), and its estimated market value was $4.5 billion in 2023, which of course also reflects the high expertise the company has in managing models, hosting them, and making them available.

What is the network that sustains this object?

• How does it move from person to person, person to software, to platform, what things are attached to it (visual culture)
• Networks of attachments
• How does it relate / sustain a collective? (human + non-human)

How does it evolve through time?

Evolution of the interface for these objects. Early chatgpt offered two parameters through the API: prompt and temperature. Today extremely complex object with all kinds of components and parameters. Visually what is the difference? Richness of the interface in decentralization (the more options, the better...)