sapienzanlp/relik-entity-linking-base
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Nicolay Rusnachenko
nicolay-r
AI & ML interests
NLP for Healthcare ⚕️ @BU_Research・PhD in NLP / IR ・Textual Information Retrieval
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6 days ago
sapienzanlp/relik-entity-linking-base
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prithivMLmods's
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9 days ago
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): https://huggingface.co/spaces/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!
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prithivMLmods's
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9 days ago
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4063
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
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9 days ago
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4180
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
9 days ago
Post
152
🚨 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
16 days ago
Post
1354
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
17 days ago
Post
224
📢 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 🔥
20 days ago
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2889
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
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20 days ago
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1838
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
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21 days ago
Post
3592
🤯 🤯 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
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21 days ago
Post
5541
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 👍
21 days ago
Post
1965
🍓 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.
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- 2 replies
replied to
ronantakizawa's
post
21 days 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.
reacted to
unmodeled-tyler's
post with 🚀
21 days ago
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3254
New Preview Model:
unmodeled-tyler/vanta-research-loux-preview
VANTA Research is excited to announce a small lab preview of our new 675B fine tune, Loux-Large. Loux is an AI model with a sophisticated, rebellious edge designed to assist and collaborate with engineers, builders, and people working on technical projects.
If you enjoy working with Loux and would like full access, let us know by liking the space or opening a discussion in the community!
VANTA Research is excited to announce a small lab preview of our new 675B fine tune, Loux-Large. Loux is an AI model with a sophisticated, rebellious edge designed to assist and collaborate with engineers, builders, and people working on technical projects.
If you enjoy working with Loux and would like full access, let us know by liking the space or opening a discussion in the community!
- 4 replies
reacted to
davidberenstein1957's
post with 🚀
21 days ago
Post
2441
🚨 Phare LLM benchmark V2: Reasoning models don't guarantee better security
Read the full blog here: https://huggingface.co/blog/davidberenstein1957/phare-llm-benchmark-v2
Read the full blog here: https://huggingface.co/blog/davidberenstein1957/phare-llm-benchmark-v2
reacted to
Reubencf's
post with 🔥
21 days ago
Post
4834
Great News !
Reubencf/Nano_Banana_Editor Now supports black-forest-labs/FLUX.1-Kontext-dev and Qwen/Qwen-Image-Edit-2509
Just log in with Huggingface and try it out
Reubencf/Nano_Banana_Editor Now supports black-forest-labs/FLUX.1-Kontext-dev and Qwen/Qwen-Image-Edit-2509
Just log in with Huggingface and try it out
replied to
ronantakizawa's
post
21 days ago
@ronantakizawa
, such a good resource for exploring the traits of the top developers under various angles!
In the context of the projects around it, I couldn't find the existing studies that were based on these data sets (which is not yet publicly available I believe).
So I was wonder, are there any potential plants where these datasets would be useful in the context of research?
reacted to
ronantakizawa's
post with 🚀
21 days ago
Post
2682
Introducing the github-top-developers dataset: A comprehensive dataset of the top 8000 developers on GitHub (2020-2025). This dataset captures the evolution of GitHub's trending developers repositories over time and the projects they work on.
#github #developers
ronantakizawa/github-top-developers
#github #developers
ronantakizawa/github-top-developers
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- 4 replies
posted
an
update
23 days ago
Post
309
📢 The second part of the tutorial series on tiny integration LLMs integration in web with streaming and batching support.
🎬️ https://youtu.be/yNKYJzlKxh0
With the second part we making step from sending data chunks ➡️ integration of LLM through the third-party providers This would be helpful to understand the minimalistic concept that is supposed to be done in order to support the streaming of large language models.
🌟 Powered by:
🧑💻 bulk-chain (inference framework): https://github.com/nicolay-r/bulk-chain
↗️ nlp-thirdgate (providers): https://github.com/nicolay-r/nlp-thirdgate
🎬️ https://youtu.be/yNKYJzlKxh0
With the second part we making step from sending data chunks ➡️ integration of LLM through the third-party providers This would be helpful to understand the minimalistic concept that is supposed to be done in order to support the streaming of large language models.
🌟 Powered by:
🧑💻 bulk-chain (inference framework): https://github.com/nicolay-r/bulk-chain
↗️ nlp-thirdgate (providers): https://github.com/nicolay-r/nlp-thirdgate
reacted to
danielhanchen's
post with 🔥
23 days ago
Post
5364
NVIDIA releases Nemotron 3 Nano, a new 30B hybrid reasoning model! 🔥
Has 1M context window & best in class performance for SWE-Bench, reasoning & chat. Run the MoE model locally with 24GB RAM.
GGUF: unsloth/Nemotron-3-Nano-30B-A3B-GGUF
💚 Step-by-step Guide: https://docs.unsloth.ai/models/nemotron-3
Has 1M context window & best in class performance for SWE-Bench, reasoning & chat. Run the MoE model locally with 24GB RAM.
GGUF: unsloth/Nemotron-3-Nano-30B-A3B-GGUF
💚 Step-by-step Guide: https://docs.unsloth.ai/models/nemotron-3
- 1 reply
reacted to
merve's
post with 👍
24 days ago
Post
7617
deepseek-ai/DeepSeek-OCR is out! 🔥 my take ⤵️
> 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