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AI & ML interests
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AFOliveiraΒ
updated a
Space 3 months ago
blackboxanalyticsΒ
posted an update 3 months ago
Post
141
Athanor Lite -- free desktop app for running local models without the setup headache
Most tools in the local AI space assume you already know your way around quantization formats, context windows, and VRAM budgets. Athanor Lite is built for the people who just want to try a model without reading a wiki first.
It scans your hardware, shows you exactly which models fit your GPU, and handles download through inference. One app, no terminal, no config files. Uses llama.cpp under the hood, wrapped in a Tauri + Rust + React desktop app.
What it does:
Hardware detection (GPU architecture, VRAM, RAM, disk)
Model catalog with fit verdicts based on your actual specs
Ollama library import (zero-copy via hardlinks)
Real-time inference HUD (tok/s, GPU %, VRAM, temperature)
Workspace system for different model/task contexts
Zero telemetry, zero accounts, zero cloud
Windows for now, Mac is next. Free and open source.
GitHub: https://github.com/BBALabs/athanor-lite
Download: https://github.com/BBALabs/athanor-lite/releases/latest
Product page: https://bbasecure.com/athanor.html
Most tools in the local AI space assume you already know your way around quantization formats, context windows, and VRAM budgets. Athanor Lite is built for the people who just want to try a model without reading a wiki first.
It scans your hardware, shows you exactly which models fit your GPU, and handles download through inference. One app, no terminal, no config files. Uses llama.cpp under the hood, wrapped in a Tauri + Rust + React desktop app.
What it does:
Hardware detection (GPU architecture, VRAM, RAM, disk)
Model catalog with fit verdicts based on your actual specs
Ollama library import (zero-copy via hardlinks)
Real-time inference HUD (tok/s, GPU %, VRAM, temperature)
Workspace system for different model/task contexts
Zero telemetry, zero accounts, zero cloud
Windows for now, Mac is next. Free and open source.
GitHub: https://github.com/BBALabs/athanor-lite
Download: https://github.com/BBALabs/athanor-lite/releases/latest
Product page: https://bbasecure.com/athanor.html
- 3 replies
burtenshawΒ
updated a
Space 4 months ago
burtenshawΒ
published a
Space 4 months ago
elismasilvaΒ
posted an update 4 months ago
Post
264
I built DOD - Deploy or Draw for the Gradio Build Small Hackathon.
It is a multiplayer UNO-style game where software incidents become card-table chaos.
Demo: build-small-hackathon/dod-uno
Repo: https://github.com/DEVAIEXP/doduno
Field Notes: https://huggingface.co/blog/elismasilva/dod-uno-en
It is a multiplayer UNO-style game where software incidents become card-table chaos.
Demo: build-small-hackathon/dod-uno
Repo: https://github.com/DEVAIEXP/doduno
Field Notes: https://huggingface.co/blog/elismasilva/dod-uno-en
mahimairajaΒ
posted an update 8 months ago
Post
1284
π₯ Qwen is dominating the SLM space right now.
We all know this year 2026 is the year of Small Models, but Alibaba team took it bit serious it seems!
Qwen3-TTS β 3-sec voice cloning, 10 languages, beats ElevenLabs
Qwen3-ASR β Just dropped TODAY! 52 languages, <8% WER, SOTA open-source ASR
Qwen-Image β #1 open-source image model on AI Arena
All Apache 2.0. The most complete open-source AI stack, period.
So, what do you think now, what next release could be? an Language Model?
Comment below
We all know this year 2026 is the year of Small Models, but Alibaba team took it bit serious it seems!
Qwen3-TTS β 3-sec voice cloning, 10 languages, beats ElevenLabs
Qwen3-ASR β Just dropped TODAY! 52 languages, <8% WER, SOTA open-source ASR
Qwen-Image β #1 open-source image model on AI Arena
All Apache 2.0. The most complete open-source AI stack, period.
So, what do you think now, what next release could be? an Language Model?
Comment below
- 1 reply
mahimairajaΒ
posted an update 9 months ago
Post
2193
My Favorite Open Source Models for Jan 2026
1. General Use - deepseek-ai/DeepSeek-V3.2
2. Reasoning - deepseek-ai/DeepSeek-V3.2-Speciale
3. Coding - Qwen/Qwen3-Coder-30B-A3B-Instruct
4. OCR - Qwen/Qwen3-VL-8B-Instruct
5. Image Generation - black-forest-labs/FLUX.2-dev
6. Image Editing - Qwen/Qwen-Image-Edit-2509
What model do you use regularly?
1. General Use - deepseek-ai/DeepSeek-V3.2
2. Reasoning - deepseek-ai/DeepSeek-V3.2-Speciale
3. Coding - Qwen/Qwen3-Coder-30B-A3B-Instruct
4. OCR - Qwen/Qwen3-VL-8B-Instruct
5. Image Generation - black-forest-labs/FLUX.2-dev
6. Image Editing - Qwen/Qwen-Image-Edit-2509
What model do you use regularly?
- 4 replies
mahimairajaΒ
posted an update 9 months ago
Post
1522
Lacking vllm support for Transformers v5, frustrating only me?
mahimairajaΒ
posted an update 9 months ago
Post
4801
Happy New Years 2026!
For next 365 days I will be commit to work on:
- Document AI and OCR Automations
- Voice Agents
- Long Running Tasks - Durable Agents
For next 365 days I will be commit to work on:
- Document AI and OCR Automations
- Voice Agents
- Long Running Tasks - Durable Agents
- 1 reply
davidquicastΒ
posted an update 10 months ago
Post
4333
- 3 replies
VyoJΒ
authored a
paper 10 months ago
elismasilvaΒ
posted an update 10 months ago
Post
555
Hey everyone,
I've built and deployed Panorama FLUX, a Gradio app for creating ultra-wide panoramic images from three different text prompts using the FLUX.1-schnell model.
It uses a custom "Mixture of Diffusers" pipeline to generate and seamlessly blend each section of the image.
Key Features:
- Multi-Prompt Input: Control the left, center, and right of the scene with unique prompts.
- Seamless Blending: Choose between Cosine and Gaussian blending methods to eliminate seams between tiles.
- Optimized for FLUX.1-schnell: Designed for fast, 4-step generation with embedded guidance.
- Multi-Language Support: On-the-fly translation for prompts written in Korean and Chinese.
- Memory Efficient: Supports both custom (mmgp) and standard diffusers offloading for use on consumer GPUs or in Spaces.
This was a fun project that involved deep-diving into the FLUX architecture to get the tiling, guidance, and positional embeddings right.
Try it out!
π Live Demo on Hugging Face Spaces:
elismasilva/flux-1-panorama
I've built and deployed Panorama FLUX, a Gradio app for creating ultra-wide panoramic images from three different text prompts using the FLUX.1-schnell model.
It uses a custom "Mixture of Diffusers" pipeline to generate and seamlessly blend each section of the image.
Key Features:
- Multi-Prompt Input: Control the left, center, and right of the scene with unique prompts.
- Seamless Blending: Choose between Cosine and Gaussian blending methods to eliminate seams between tiles.
- Optimized for FLUX.1-schnell: Designed for fast, 4-step generation with embedded guidance.
- Multi-Language Support: On-the-fly translation for prompts written in Korean and Chinese.
- Memory Efficient: Supports both custom (mmgp) and standard diffusers offloading for use on consumer GPUs or in Spaces.
This was a fun project that involved deep-diving into the FLUX architecture to get the tiling, guidance, and positional embeddings right.
Try it out!
π Live Demo on Hugging Face Spaces:
elismasilva/flux-1-panorama
elismasilvaΒ
posted an update 11 months ago
Post
2619
I'm thrilled to launch SUP Toolbox! An AI tool for image restoration & upscaling using SUPIR, FaithDiff & ControlUnion. Built with Diffusers and Gradio UI featuring 14 custom components I developed.
Space Demo: elismasilva/sup-toolbox-app
App repository: https://github.com/DEVAIEXP/sup-toolbox-app
CLI repository: https://github.com/DEVAIEXP/sup-toolbox
Feedback is welcome!
Space Demo: elismasilva/sup-toolbox-app
App repository: https://github.com/DEVAIEXP/sup-toolbox-app
CLI repository: https://github.com/DEVAIEXP/sup-toolbox
Feedback is welcome!
- 2 replies
burtenshawΒ
authored a
paper about 1 year ago
burtenshawΒ
posted an update about 1 year ago
Post
10302
Smol course has a distinctive approach to teaching post-training, so I'm posting about how itβs different to other post-training courses, including the llm course thatβs already available.
In short, the smol course is just more direct that any of the other course, and intended for semi-pro post trainers.
- Itβs a minimal set of instructions on the core parts.
- Itβs intended to bootstrap real projects you're working on.
- The material handsover to existing documentation for details
- Likewise, it handsover to the LLM course for basics.
- Assessment is based on a leaderboard, without reading all the material.
To start the smol course, follow here:
smol-course
In short, the smol course is just more direct that any of the other course, and intended for semi-pro post trainers.
- Itβs a minimal set of instructions on the core parts.
- Itβs intended to bootstrap real projects you're working on.
- The material handsover to existing documentation for details
- Likewise, it handsover to the LLM course for basics.
- Assessment is based on a leaderboard, without reading all the material.
To start the smol course, follow here:
burtenshawΒ
posted an update about 1 year ago
Post
5735
new smol course
If youβre building with or learning about post training AI models right now, we have a new FREE and CERTIFIED course.
π Follow the org to join in smol-course
The course builds on smol course v1 which was the fastest way to learn to train your custom AI models. It now has:
- A leaderboard for students to submit models to
- Certification based on exams and leaderboards
- Prizes based on Leaderboards
- Up to date content on TRL and SmolLM3
- Deep integration with the Hubβs compute for model training and evaluation
We will release chapters every few weeks, so you can follow the org to stay updated.
If youβre building with or learning about post training AI models right now, we have a new FREE and CERTIFIED course.
π Follow the org to join in
The course builds on smol course v1 which was the fastest way to learn to train your custom AI models. It now has:
- A leaderboard for students to submit models to
- Certification based on exams and leaderboards
- Prizes based on Leaderboards
- Up to date content on TRL and SmolLM3
- Deep integration with the Hubβs compute for model training and evaluation
We will release chapters every few weeks, so you can follow the org to stay updated.
- 2 replies
burtenshawΒ
posted an update about 1 year ago
Post
3325
The open source AI community is just made of people who are passionate and care about their work. So we thought it would be cool to share our favourite icons of the community with a fun award.
Winners get free Hugging Face Pro Subscriptions, Merchandise, or compute credits for the hub.
π Follow and nominate here:
community-spotlight
This is a new initiative to recognise and celebrate the incredible work being done by community members. It's all about inspiring more collaboration and innovation in the world of machine learning and AI.
They're highlighting contributors in four key areas:
- model creators: building and sharing innovative and state-of-the-art models.
- educators: sharing knowledge through posts, articles, demos, and events.
- tool builders: creating the libraries, frameworks, and applications that we all use.
- community champions: supporting and mentoring others in forums.
Know someone who deserves recognition? Nominate them by opening a post in the Hugging Face community forum.
Winners get free Hugging Face Pro Subscriptions, Merchandise, or compute credits for the hub.
π Follow and nominate here:
This is a new initiative to recognise and celebrate the incredible work being done by community members. It's all about inspiring more collaboration and innovation in the world of machine learning and AI.
They're highlighting contributors in four key areas:
- model creators: building and sharing innovative and state-of-the-art models.
- educators: sharing knowledge through posts, articles, demos, and events.
- tool builders: creating the libraries, frameworks, and applications that we all use.
- community champions: supporting and mentoring others in forums.
Know someone who deserves recognition? Nominate them by opening a post in the Hugging Face community forum.
- 1 reply
davidquicastΒ
posted an update about 1 year ago
Post
2906
Just applied for HF Community Grant for βHugging Researchβ β a lightweight CodeAgentβbased research assistant built on Hugging Faceβs Open Deep Research project for the Hugging Face Hub (models, datasets, Spaces, users, collections, papers). It gathers links via dedicated tools and organizes them for easy review.
As this is for the community, comments and suggestions are appreciated: https://huggingface.co/spaces/daqc/hugging-research/discussions/1#68a94d9bcb035c54bc671119
As this is for the community, comments and suggestions are appreciated: https://huggingface.co/spaces/daqc/hugging-research/discussions/1#68a94d9bcb035c54bc671119
VyoJΒ
authored a
paper about 1 year ago
elismasilvaΒ
posted an update about 1 year ago
Post
399
Building settings panels in? I created "PropertySheet", a new gradio component that turns your Python dataclass into a full UI! β‘οΈ
β Sliders, dropdowns, color pickers & more
β Collapsible groups
β Reset buttons & tooltips
elismasilva/gradio_propertysheet
β Sliders, dropdowns, color pickers & more
β Collapsible groups
β Reset buttons & tooltips
elismasilva/gradio_propertysheet