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AI & ML interests
AI agents, open-weight models, machine learning, MLOps, developer tools, AI automation, and AI-assisted publishing.
Recent Activity
repliedto sequelbox's post about 2 hours ago NEW RELEASES for the new Muse Glimmer 30B!
- Esper 4, our flagship agentic coder: specialist in coding, architecture, DevOps, and MLOps!
- Tachibana-Agent, trained only on code for dedicated, predictable deployment!
GET OUR NEW MODELS:
https://huggingface.co/ValiantLabs/Muse-Glimmer-30B-Esper4
https://huggingface.co/sequelbox/Muse-Glimmer-30B-Tachibana-Agent
Get the datasets for your own training:
https://huggingface.co/datasets/sequelbox/Titanium4-DeepSeek-V4-Pro
https://huggingface.co/datasets/sequelbox/Mitakihara2-DeepSeek-V4-Pro
https://huggingface.co/datasets/sequelbox/Tachibana4-DeepSeek-V4-Pro
We'll be expanding Esper 4 to more models and releasing new models as funding allows - donate for more, faster, better models and datasets: https://huggingface.co/spaces/sequelbox/SupportOpenSource
Also, starting work on the SV4 datasets :)
More to come soon!
love,
allegra repliedto dronefreak's post about 5 hours ago 🌧️❄️ Free demo: remove rain, raindrops, or snow from a photo with a single model
I put together an unofficial demo for **Histoformer** (ECCV 2024, arXiv: 2407.10172), a 16.6M-parameter transformer that handles three different weather degradations, rain streaks, adherent raindrops, and snow, in one unified model. It uses a "histogram self-attention" mechanism that groups pixels by degradation intensity instead of spatial position, which is a
neat way to sidestep the usual spatial-window tradeoffs in restoration transformers.
Try it here, free on ZeroGPU: https://huggingface.co/spaces/dronefreak/histoformer-weather-restoration
Upload a photo and get a before/after slider. Two checkpoints available: one tuned for real-world photos, one for the paper's synthetic benchmarks.
Also put together a cleaner, easy-to-use model card with a copy-pasteable Quickstart if you'd rather run it yourself: https://huggingface.co/dronefreak/Histoformer
This is an unofficial demo/mirror, not affiliated with the original authors. All credit for the actual research goes to Shangquan Sun, Wenqi Ren, Xinwei Gao, Rui Wang, and Xiaochun Cao (@sunsean). Official repo: https://github.com/sunshangquan/Histoformer. Weights are MIT-licensed.
Reported numbers from the paper: 32.1 PSNR on rain+fog (Outdoor-Rain), 33.1 on raindrops, 37.4 / 32.2 on light/heavy snow (Snow100K-S/L). repliedto maglun's post about 8 hours ago Inspect model quantization in the browser, without download
Curious how models on Hugging Face spend their "bit budget"? A few days ago I shared the first version of a little tool I built out of my own curiosity (and for fun). Since then, thanks in large part to great feedback from people here, a lot has changed.
New in the last few days:
- GGUF support - handy with all the new great GGUF quants
- Decode for AWQ, GPTQ, NF4, mxfp4 packed experts, packed-int32, and additive-codebook formats
- Improved comparison view for diffing two quants of the same model
- Built-in anonymous report-issue button connecting a report to specific model
- plus many small fixes
After my first post I got great feedback from several community members, and some issues were fixed within hours. I'm planning an acknowledgments section on the site, and when you report an issue you get a receipt ID you can keep to claim credit later. (reports are anonymous by design; I store no identity, so the receipt hash works like a bearer token for your find)
It's still very much a side project I hope others find useful. Explore any HF model in the browser without downloading it, the webpage reads from the safetensors header via a range request, and only tensors you click stream, and large ones are sampled, not downloaded in full. And there is a report button right in the tool when things don’t look right.
Feedback very welcome, especially models that break it :) Or ideas on what is missing.
https://tensorlens.dev
(screenshot attached from viewing one of Unsloth's GGUF quants) Organizations
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