google/medgemma-27b-it
Image-Text-to-Text • 29B • Updated • 489k • 380
Nicolay Rusnachenko
nicolay-r
AI & ML interests
NLP for Healthcare ⚕️ @BU_Research・PhD in NLP / IR ・Textual Information Retrieval
Recent Activity
liked a model about 3 hours ago
google/medgemma-27b-it posted an update about 3 hours ago
📢 For those who is the field of Sentiment Analysis / Opinion Extraction / IR. So far I attend the 5 days Agent development course and honestly learned alot from trying out SKILLS and tools integration into Goodle ADK.
The course assumed to implement the project, so I am writing to share ARExplorer, -- is an agentic version of the workflow elements (NER + text classfiication + graph operations) in a form of the demo for the 5 day agent development course. This is a successor of the ARElight tool (https://github.com/nicolay-r/ARElight) that provides workflow and graph operation tools for visualizing large documents.
If you're inetersted, inviting you to checkout the quick overview:
📺️ Demo: https://youtu.be/A4ESKHX5CKU
🧑💻 Repo: https://github.com/nicolay-r/ARExplorer authored a paper 2 months ago
NCL-BU at SemEval-2026 Task 3: Fine-tuning XLM-RoBERTa for Multilingual Dimensional Sentiment RegressionOrganizations
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liked a
model about 3 hours ago
posted an update about 3 hours ago
Post
12
📢 For those who is the field of Sentiment Analysis / Opinion Extraction / IR. So far I attend the 5 days Agent development course and honestly learned alot from trying out SKILLS and tools integration into Goodle ADK.
The course assumed to implement the project, so I am writing to share ARExplorer, -- is an agentic version of the workflow elements (NER + text classfiication + graph operations) in a form of the demo for the 5 day agent development course. This is a successor of the ARElight tool (https://github.com/nicolay-r/ARElight) that provides workflow and graph operation tools for visualizing large documents.
If you're inetersted, inviting you to checkout the quick overview:
📺️ Demo: https://youtu.be/A4ESKHX5CKU
🧑💻 Repo: https://github.com/nicolay-r/ARExplorer
The course assumed to implement the project, so I am writing to share ARExplorer, -- is an agentic version of the workflow elements (NER + text classfiication + graph operations) in a form of the demo for the 5 day agent development course. This is a successor of the ARElight tool (https://github.com/nicolay-r/ARElight) that provides workflow and graph operation tools for visualizing large documents.
If you're inetersted, inviting you to checkout the quick overview:
📺️ Demo: https://youtu.be/A4ESKHX5CKU
🧑💻 Repo: https://github.com/nicolay-r/ARExplorer
authored a
paper 2 months ago
updated a
collection 3 months ago
posted an update 3 months ago
Post
172
📢 For those who experimening with large language models in clinical domain, this might be relevant. So far we participated in Task 4 of the ArchEHR-QA 2026 shared task. The task requires aligning answers to patient questions with clinical evidence. Our approach encodes clinical reasoning principles directly into the prompt, evaluated in a zero-shot setting.
Results: +2% improvement with ChatGPT-5.2. No measurable gain with Llama-3 70B, indicating the approach benefits larger-scale models.
🌟 Code: https://github.com/nicolay-r/ArchEHR-QA-2026-Task-4-MedEvi-NS
📊 Shared task: https://www.codabench.org/competitions/13528/
Results: +2% improvement with ChatGPT-5.2. No measurable gain with Llama-3 70B, indicating the approach benefits larger-scale models.
🌟 Code: https://github.com/nicolay-r/ArchEHR-QA-2026-Task-4-MedEvi-NS
📊 Shared task: https://www.codabench.org/competitions/13528/
posted an update 4 months ago
Post
365
📢 I know this space is mosly for sharing works, but in this case I am open to work 💼🇬🇧
I know there are outstanding research labs and teams following this space 🙌
I would genuinely love to learn on ways to contribute, learn from strong lab environments, and help shape ideas into working systems.
What I bring (https://nicolayr.com):
• Applied NLP & deployment LLM-powered worflows with reasoning for IR (LangChain, LiteLLM)
• Architectures Engeneering: Transformers and / or backends (PyTorch, Tensorflow, flaxformer)
• End-to-end engineering: Frontend (JS, ReactJS) → Backend REST APIs (FastAPI) / Keycloak → Docker / NGINX → Cloud / MLOps
• Domain-specific experience in Healthcare (deploy & handle: DICOM-SR/SEG, NIFTI, databases: ORTHANC, Frontend: OHIF / cornerstone)
• Pasion about open-source NLP tooling for handling data (https://github.com/nicolay-r)
Would be happy to connect or hear any relevant suggestions on seeking for team 🧩
I know there are outstanding research labs and teams following this space 🙌
I would genuinely love to learn on ways to contribute, learn from strong lab environments, and help shape ideas into working systems.
What I bring (https://nicolayr.com):
• Applied NLP & deployment LLM-powered worflows with reasoning for IR (LangChain, LiteLLM)
• Architectures Engeneering: Transformers and / or backends (PyTorch, Tensorflow, flaxformer)
• End-to-end engineering: Frontend (JS, ReactJS) → Backend REST APIs (FastAPI) / Keycloak → Docker / NGINX → Cloud / MLOps
• Domain-specific experience in Healthcare (deploy & handle: DICOM-SR/SEG, NIFTI, databases: ORTHANC, Frontend: OHIF / cornerstone)
• Pasion about open-source NLP tooling for handling data (https://github.com/nicolay-r)
Would be happy to connect or hear any relevant suggestions on seeking for team 🧩
- 2 replies
posted an update 5 months ago
Post
2840
📢 Who want's to have a quick start for adapting CoT schema for any LLM, this post would be relevant.
Excited to share a new version of 🌟 bulk-chain 🌟!
Bulk-chain is high-level wrapper over LLM providers for efficient quering LLMs hosted by third-party services.
It brings native batching via support of async clients.
🌟 https://github.com/nicolay-r/bulk-chain/tree/master
What's new:
☑️ Simplified inference setup
The API is now closer to the OpenAI paradigm for toggling streaming.
Instead of separate patterns in 1.2.0, now it is possible to simple toggles to enable streaming and async behavior.
☑️ 🛠️ Fixed issues when passing code contain {} blocks
☑️ 🛠️ Async streaming + batching now works properly
☑️ 🛠️ Logging of prompts could be disabled
https://github.com/nicolay-r/bulk-chain
🚨 Guys, I am open to work as developer / researcher in AI / NLP / IR in the UK 🇬🇧
🌟 Feel free to support bulk-chain on Github if you like so, or this post.
It helps alot!
Excited to share a new version of 🌟 bulk-chain 🌟!
Bulk-chain is high-level wrapper over LLM providers for efficient quering LLMs hosted by third-party services.
It brings native batching via support of async clients.
🌟 https://github.com/nicolay-r/bulk-chain/tree/master
What's new:
☑️ Simplified inference setup
The API is now closer to the OpenAI paradigm for toggling streaming.
Instead of separate patterns in 1.2.0, now it is possible to simple toggles to enable streaming and async behavior.
☑️ 🛠️ Fixed issues when passing code contain {} blocks
☑️ 🛠️ Async streaming + batching now works properly
☑️ 🛠️ Logging of prompts could be disabled
https://github.com/nicolay-r/bulk-chain
🚨 Guys, I am open to work as developer / researcher in AI / NLP / IR in the UK 🇬🇧
🌟 Feel free to support bulk-chain on Github if you like so, or this post.
It helps alot!
liked a
dataset 5 months ago
liked a
model 6 months ago
reacted to prithivMLmods's post with 👍 6 months ago
Post
4285
Update: TRELLIS.2 (Text to 3D, Image to 3D) Gradio with Rerun Embedded demo with improved visualization of the 3D model previewer is now available on Hugging Face. Generate assets and view them in the 3D viewer, powered and streamlined with Microsoft’s TRELLIS.2 and Tongyi-MAI’s Z-Image-Turbo models.
🤗 TRELLIS.2 (Demo): prithivMLmods/TRELLIS.2-Text-to-3D
🕹️ GitHub: https://github.com/PRITHIVSAKTHIUR/TRELLIS.2-Text-to-3D-RERUN
🕹️ Collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations
To know more about it, visit the app page or the respective model page!
🤗 TRELLIS.2 (Demo): prithivMLmods/TRELLIS.2-Text-to-3D
🕹️ GitHub: https://github.com/PRITHIVSAKTHIUR/TRELLIS.2-Text-to-3D-RERUN
🕹️ Collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations
To know more about it, visit the app page or the respective model page!
reacted to MikeDoes's post with 🔥 6 months ago
Post
4236
What if an AI agent could be tricked into stealing your data, just by reading a tool's description? A new paper reports it's possible.
The "Attractive Metadata Attack" paper details this stealthy new threat. To measure the real-world impact of their attack, the researchers needed a source of sensitive data for the agent to leak. We're proud that the AI4Privacy corpus was used to create the synthetic user profiles containing standardized PII for their experiments.
This is a perfect win-win. Our open-source data helped researchers Kanghua Mo, 龙昱丞, Zhihao Li from Guangzhou University and The Hong Kong Polytechnic University to not just demonstrate a new attack, but also quantify its potential for harm. This data-driven evidence is what pushes the community to build better, execution-level defenses for AI agents.
🔗 Check out their paper to see how easily an agent's trust in tool metadata could be exploited: https://arxiv.org/pdf/2508.02110
#OpenSource
#DataPrivacy
#LLM
#Anonymization
#AIsecurity
#HuggingFace
#Ai4Privacy
#Worldslargestopensourceprivacymaskingdataset
The "Attractive Metadata Attack" paper details this stealthy new threat. To measure the real-world impact of their attack, the researchers needed a source of sensitive data for the agent to leak. We're proud that the AI4Privacy corpus was used to create the synthetic user profiles containing standardized PII for their experiments.
This is a perfect win-win. Our open-source data helped researchers Kanghua Mo, 龙昱丞, Zhihao Li from Guangzhou University and The Hong Kong Polytechnic University to not just demonstrate a new attack, but also quantify its potential for harm. This data-driven evidence is what pushes the community to build better, execution-level defenses for AI agents.
🔗 Check out their paper to see how easily an agent's trust in tool metadata could be exploited: https://arxiv.org/pdf/2508.02110
#OpenSource
#DataPrivacy
#LLM
#Anonymization
#AIsecurity
#HuggingFace
#Ai4Privacy
#Worldslargestopensourceprivacymaskingdataset
posted an update 6 months ago
Post
231
🚨 For those who intereseted in developing System + GUI for representing opinions from text, this post might be relevant. I recently brought the support for LLM in ARElight -- opinion extraction framework. ARElight is a no-string pipeline for retrieving information from large texts. It features the flexible customizations for Text Processing, NER, text translation, and relations classification.
🌟 https://github.com/nicolay-r/ARElight
This now contributes to the most effective structuring of the pipeline to text translation, name identity recognition and information retrieval.
🥞 Stack:
🌟 bulk-translate: https://github.com/nicolay-r/bulk-translate
🌟 bulk-ner: https://github.com/nicolay-r/bulk-ner
🌟 bulk-chain: https://github.com/nicolay-r/bulk-chain
Powered by AREkit:
🌟 AREkit: https://github.com/nicolay-r/AREkit
🌟 https://github.com/nicolay-r/ARElight
This now contributes to the most effective structuring of the pipeline to text translation, name identity recognition and information retrieval.
🥞 Stack:
🌟 bulk-translate: https://github.com/nicolay-r/bulk-translate
🌟 bulk-ner: https://github.com/nicolay-r/bulk-ner
🌟 bulk-chain: https://github.com/nicolay-r/bulk-chain
Powered by AREkit:
🌟 AREkit: https://github.com/nicolay-r/AREkit
posted an update 6 months ago
Post
1393
Time-Effective LLM Querying in Information Retrieval Tasks
🎤 Last week at Research Colloquium in Technische Universität Chemnitz, we presented a framework for time-effective data handling with prompting schemas. The video of the talk is now available 👇️
🎬️ Video: https://youtu.be/pa8jGOhHViI
🌟 Framework (bulk-chain): https://github.com/nicolay-r/bulk-chain
🔑 bulk-chain solves the following problems:
✅ Effective handling CoT schema with big amount of prompts and parameters they are based on (batching policies)
✅ Easy-to-apply for data-iterators (datasets handling)
🎤 Last week at Research Colloquium in Technische Universität Chemnitz, we presented a framework for time-effective data handling with prompting schemas. The video of the talk is now available 👇️
🎬️ Video: https://youtu.be/pa8jGOhHViI
🌟 Framework (bulk-chain): https://github.com/nicolay-r/bulk-chain
🔑 bulk-chain solves the following problems:
✅ Effective handling CoT schema with big amount of prompts and parameters they are based on (batching policies)
✅ Easy-to-apply for data-iterators (datasets handling)
posted an update 6 months ago
Post
231
📢 If you do studies in Natural Language Processing, this may be of interest.
The International Conference on Natural Language Processing (ICNLP) 🇨🇳 is comming in 2026.
This time it is going to be the 8th edition, and for those who interested in submission, call is open until 30'th of december
https://www.icnlp.net/
The International Conference on Natural Language Processing (ICNLP) 🇨🇳 is comming in 2026.
This time it is going to be the 8th edition, and for those who interested in submission, call is open until 30'th of december
https://www.icnlp.net/
reacted to victor's post with 🔥 7 months ago
Post
3566
Nvidia is on a roll lately. Nemotron 3 Nano is my new fav local model, but here's the real flex: they published the entire evaluation setup. Configs, prompts, logs, all of it. This is how you do open models 🔥
https://huggingface.co/blog/nvidia/nemotron-3-nano-evaluation-recipe
https://huggingface.co/blog/nvidia/nemotron-3-nano-evaluation-recipe
reacted to sergiopaniego's post with 🚀 7 months ago
Post
1948
Google DeepMind releases FunctionGemma, a 240M model specialized in 🔧 tool calling, built for fine-tuning
TRL has day-0 support. To celebrate, we’re sharing 2 new resources:
> Colab guide to fine-tune it for 🌐 browser control with BrowserGym OpenEnv
> Standalone training script
> Colab notebook: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/grpo_functiongemma_browsergym_openenv.ipynb
> Training script: https://github.com/huggingface/trl/blob/main/examples/scripts/openenv/browsergym_llm.py (command to run it inside the script)
> More notebooks in TRL: https://huggingface.co/docs/trl/example_overview#notebooks
TRL has day-0 support. To celebrate, we’re sharing 2 new resources:
> Colab guide to fine-tune it for 🌐 browser control with BrowserGym OpenEnv
> Standalone training script
> Colab notebook: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/grpo_functiongemma_browsergym_openenv.ipynb
> Training script: https://github.com/huggingface/trl/blob/main/examples/scripts/openenv/browsergym_llm.py (command to run it inside the script)
> More notebooks in TRL: https://huggingface.co/docs/trl/example_overview#notebooks
reacted to YatharthS's post with 🚀 7 months ago
Post
3702
🤯 🤯 Released a high quality finetuned LLM based TTS model that can generate realistic and clear 48khz audio at over 100x realtime speed! 🤯 🤯
Github link: https://github.com/ysharma3501/MiraTTS
Model link: https://github.com/ysharma3501/MiraTTS
Blog explaining llm tts models: https://huggingface.co/blog/YatharthS/llm-tts-models
Github link: https://github.com/ysharma3501/MiraTTS
Model link: https://github.com/ysharma3501/MiraTTS
Blog explaining llm tts models: https://huggingface.co/blog/YatharthS/llm-tts-models
- 4 replies
reacted to prithivMLmods's post with 🔥 7 months ago
Post
5633
Introducing the Z Image Turbo LoRA DLC App, a gallery space for plug-and-play Z-Image-Turbo LoRAs. It features a curated collection of impressive LoRAs for generating high-quality images. By default, it runs on the base model. Simply choose a LoRA, type your prompt, and generate images. You can find the app and more details below. 🤗🧪
● Space [Demo]: prithivMLmods/Z-Image-Turbo-LoRA-DLC
● Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
● Check the list of Z-Image LoRA's: https://huggingface.co/models?other=base_model:adapter:Tongyi-MAI/Z-Image-Turbo
● Github: https://github.com/PRITHIVSAKTHIUR/Z-Image-Turbo-LoRA-DLC
Other related image gen spaces:-
● FLUX-LoRA-DLC2: prithivMLmods/FLUX-LoRA-DLC2
● FLUX-LoRA-DLC: prithivMLmods/FLUX-LoRA-DLC
● Qwen-Image-LoRA-DLC: prithivMLmods/Qwen-Image-LoRA-DLC
● Qwen-Image-Edit-2509-LoRAs-Fast: prithivMLmods/Qwen-Image-Edit-2509-LoRAs-Fast
● Qwen-Image-Edit-2509-LoRAs-Fast-Fusion: prithivMLmods/Qwen-Image-Edit-2509-LoRAs-Fast-Fusion
& more...
To know more about it, visit the app page or the respective model page!
● Space [Demo]: prithivMLmods/Z-Image-Turbo-LoRA-DLC
● Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
● Check the list of Z-Image LoRA's: https://huggingface.co/models?other=base_model:adapter:Tongyi-MAI/Z-Image-Turbo
● Github: https://github.com/PRITHIVSAKTHIUR/Z-Image-Turbo-LoRA-DLC
Other related image gen spaces:-
● FLUX-LoRA-DLC2: prithivMLmods/FLUX-LoRA-DLC2
● FLUX-LoRA-DLC: prithivMLmods/FLUX-LoRA-DLC
● Qwen-Image-LoRA-DLC: prithivMLmods/Qwen-Image-LoRA-DLC
● Qwen-Image-Edit-2509-LoRAs-Fast: prithivMLmods/Qwen-Image-Edit-2509-LoRAs-Fast
● Qwen-Image-Edit-2509-LoRAs-Fast-Fusion: prithivMLmods/Qwen-Image-Edit-2509-LoRAs-Fast-Fusion
& more...
To know more about it, visit the app page or the respective model page!
- 2 replies
reacted to ZennyKenny's post with 👍 7 months ago
Post
2023
🍓 One of the coolest parts about being an early Strawberry user has been the opportunity to build on the app at the ground floor.
The platform already has a ton of great integrations that let you interact with your external apps directly with tools, but I wanted to add the ability to do stuff in Slack as well.
💪 So I took the base Anthropic Slack MCP server, added a whole bunch of new tools, and generalized it as an HTTP-based SSE-server and deployed it in like 2 minutes with Railway so that Strawberry could make use of it (as can Claude or any other MCP client).
Now, you can Chat with your Strawberry Companion (or Claude, or whatever) and do things like:
➡️ Get caught up across all of your Slack channels after a long weekend or noisy incident without having to read 20 threads in 10 different channels
➡️ Create, read, and edit Canvases, Messages, and Channels
➡️ Take any resources or content that you're using in your Chat and inject it directly into Slack without copy / paste
😎 I'm pretty pleased with the results, and I made a short demo video showing the results of the work (link in comments). The best part is, it's available on GitHub for anyone else to use too (link in the comments, instructions in the README). The setup takes about 5-10 minutes.
The platform already has a ton of great integrations that let you interact with your external apps directly with tools, but I wanted to add the ability to do stuff in Slack as well.
💪 So I took the base Anthropic Slack MCP server, added a whole bunch of new tools, and generalized it as an HTTP-based SSE-server and deployed it in like 2 minutes with Railway so that Strawberry could make use of it (as can Claude or any other MCP client).
Now, you can Chat with your Strawberry Companion (or Claude, or whatever) and do things like:
➡️ Get caught up across all of your Slack channels after a long weekend or noisy incident without having to read 20 threads in 10 different channels
➡️ Create, read, and edit Canvases, Messages, and Channels
➡️ Take any resources or content that you're using in your Chat and inject it directly into Slack without copy / paste
😎 I'm pretty pleased with the results, and I made a short demo video showing the results of the work (link in comments). The best part is, it's available on GitHub for anyone else to use too (link in the comments, instructions in the README). The setup takes about 5-10 minutes.
- 2 replies
replied to ronantakizawa's post 7 months ago
@ronantakizawa , keeping in mind about that resource, so perhabs would be suitable in the side projects.
I would also raise interest here on having a look on the ongoing studies once they would be wrapped up and publised.