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Exploring foundation models for DNA and beyond π§¬
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tfrereΒ
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Space 6 days ago
kashifΒ
updated a
model 8 days ago
lvwerraΒ
published a
Space 8 days ago
lewtunΒ
updated a
model 8 days ago
kashifΒ
updated 3
models 14 days ago
lewtunΒ
submitted 2
papers to Daily Papers 4 months ago
Post
2118
πππHuge biotech data drop todayπππ
The largest drug-target dataset ever created was just released on Hugging Faceβand it's still growing...
EvE Bio is further updating the dataset every 8 weeks. Drug development dream.
Read the blog: https://huggingface.co/blog/hugging-science/eve-bio-mapping-the-pharmone-drug-interaction
Play with the data: eve-bio/drug-target-activity
The largest drug-target dataset ever created was just released on Hugging Faceβand it's still growing...
EvE Bio is further updating the dataset every 8 weeks. Drug development dream.
Read the blog: https://huggingface.co/blog/hugging-science/eve-bio-mapping-the-pharmone-drug-interaction
Play with the data: eve-bio/drug-target-activity
abidlabsΒ
authored 3
papers 7 months ago
Persistent Anti-Muslim Bias in Large Language Models
Paper β’ 2101.05783 β’ Published β’ 4
STG-MTL: Scalable Task Grouping for Multi-Task Learning Using Data Map
Paper β’ 2307.03374 β’ Published β’ 2
Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild
Paper β’ 1906.02569 β’ Published β’ 2
Post
11420
Why I think local, open-source models will eventually win.
The most useful AI applications are moving toward multi-turn agentic behavior: systems that take hundreds or even thousands of iterative steps to complete a task, e.g. Claude Code, computer-control agents that click, type, and test repeatedly.
In these cases, the power of the model is not how smart it is per token, but in how quickly it can interact with its environment and tools across many steps. In that regime, model quality becomes secondary to latency.
An open-source model that can call tools quickly, check that the right thing was clicked, or verify that a code change actually passes tests can easily outperform a slightly βsmarterβ closed model that has to make remote API calls for every move.
Eventually, the balance tips: it becomes impractical for an agent to rely on remote inference for every micro-action. Just as no one would tolerate a keyboard that required a network request per keystroke, users wonβt accept agent workflows bottlenecked by latency. All devices will ship with local, open-source models that are βgood enoughβ and the expectation will shift toward everything running locally. Itβll happen sooner than most people think.
The most useful AI applications are moving toward multi-turn agentic behavior: systems that take hundreds or even thousands of iterative steps to complete a task, e.g. Claude Code, computer-control agents that click, type, and test repeatedly.
In these cases, the power of the model is not how smart it is per token, but in how quickly it can interact with its environment and tools across many steps. In that regime, model quality becomes secondary to latency.
An open-source model that can call tools quickly, check that the right thing was clicked, or verify that a code change actually passes tests can easily outperform a slightly βsmarterβ closed model that has to make remote API calls for every move.
Eventually, the balance tips: it becomes impractical for an agent to rely on remote inference for every micro-action. Just as no one would tolerate a keyboard that required a network request per keystroke, users wonβt accept agent workflows bottlenecked by latency. All devices will ship with local, open-source models that are βgood enoughβ and the expectation will shift toward everything running locally. Itβll happen sooner than most people think.
- 8 replies
Post
13028
deepseek-ai/DeepSeek-OCR is out! π₯ my take ‡οΈ
> pretty insane it can parse and re-render charts in HTML
> it uses CLIP and SAM features concatenated, so better grounding
> very efficient per vision tokens/performance ratio
> covers 100 languages
> pretty insane it can parse and re-render charts in HTML
> it uses CLIP and SAM features concatenated, so better grounding
> very efficient per vision tokens/performance ratio
> covers 100 languages
- 4 replies
thomwolfΒ
authored a
paper 8 months ago
lvwerraΒ
authored a
paper 8 months ago
Post
1614
What other features would you like to see on the Trackio Dashboard? ( gradio-templates/trackio-dashboard)
Post
7046
large AI labs open-sourced a ton of models last week π₯
here's few picks, find even more here merve/sep-16-releases-68d13ea4c547f02f95842f05 π€
> IBM released a new Docling model with 258M params based on Granite (A2.0) π ibm-granite/granite-docling-258M
> Xiaomi released 7B audio LM with base and instruct variants (MIT) XiaomiMiMo/mimo-audio-68cc7202692c27dae881cce0
> DecartAI released Lucy Edit, open Nano Banana π (NC) decart-ai/Lucy-Edit-Dev
> OpenGVLab released a family of agentic computer use models (3B/7B/32B) with the dataset π» OpenGVLab/scalecua-68c912cf56f7ff4c8e034003
> Meituan Longcat released thinking version of LongCat-Flash π meituan-longcat/LongCat-Flash-Thinking
here's few picks, find even more here merve/sep-16-releases-68d13ea4c547f02f95842f05 π€
> IBM released a new Docling model with 258M params based on Granite (A2.0) π ibm-granite/granite-docling-258M
> Xiaomi released 7B audio LM with base and instruct variants (MIT) XiaomiMiMo/mimo-audio-68cc7202692c27dae881cce0
> DecartAI released Lucy Edit, open Nano Banana π (NC) decart-ai/Lucy-Edit-Dev
> OpenGVLab released a family of agentic computer use models (3B/7B/32B) with the dataset π» OpenGVLab/scalecua-68c912cf56f7ff4c8e034003
> Meituan Longcat released thinking version of LongCat-Flash π meituan-longcat/LongCat-Flash-Thinking
- 2 replies
Post
3559
IBM just released small swiss army knife for the document models: granite-docling-258M on Hugging Face π₯
> not only a document converter but also can do document question answering, understand multiple languages π€―
> best part: released with Apache 2.0 license π use it with your commercial projects!
> it supports transformers, vLLM and MLX from the get-go! π€
> built on SigLIP2 & granite-165M
model: ibm-granite/granite-docling-258M
demo: ibm-granite/granite-docling-258m-demo π
> not only a document converter but also can do document question answering, understand multiple languages π€―
> best part: released with Apache 2.0 license π use it with your commercial projects!
> it supports transformers, vLLM and MLX from the get-go! π€
> built on SigLIP2 & granite-165M
model: ibm-granite/granite-docling-258M
demo: ibm-granite/granite-docling-258m-demo π