Yeah seems very cool, great work!
Yatharth Sharma
YatharthS
AI & ML interests
TTS, speech generation, Agents, MCP
Recent Activity
updated
a Space
about 17 hours ago
YatharthS/NovaSR
replied to
their
post
1 day ago
I just released NovaSR, a tiny 52kb audio upsampler that can enhance 3600 seconds of muffled 16khz audio in to clearer 48khz audio in just 1 second!
NovaSR can
- Enhance TTS model quality.
- Restore poor quality datasets.
- Work on any device(just 52kb which is smaller than a 3 second audio file!)
Model: https://huggingface.co/YatharthS/NovaSR
Space to try it: https://huggingface.co/spaces/YatharthS/NovaSR
Github repo: https://github.com/ysharma3501/NovaSR
liked
a model
1 day ago
MihaiPopa-1/TinySR
Organizations
replied to
their
post
1 day ago
reacted to
Ujjwal-Tyagi's
post with 🤗
3 days ago
Post
2510
I am very excited to see the release of
nyuuzyou/gitee-code. This is exactly what I have been looking for. Thank you to
@nyuuzyou
for his hard work on this.
- 3 replies
reacted to
dhruv3006's
post with 👀
3 days ago
Post
2648
Voiden gives you two ways to work with GraphQL - so you can focus on writing and testing queries with confidence.
1. Importing a GraphQL Schema File
You can import a GraphQL schema file such as .graphql or .gql directly into Voiden.
When you do this:
- Voiden reads all types, queries, mutations, and subscriptions from the schema
- The schema becomes available locally and works well in offline scenarios
- You get a stable, version-controlled setup that aligns nicely with Git workflows
This approach is ideal when you already have the schema file and want full control over it.
2. Using GraphQL Introspection
Alternatively, you can provide a GraphQL endpoint URL to Voiden.
In this case :
- Voiden make an introspection query to the GraphQL server
- The server returns all available types, queries, mutations, and subscriptions
- Voiden automatically loads this information so you can start querying immediately
This option is perfect for quickly exploring a live GraphQL API or when the schema file is not available locally.
Use GraphQL in our beta version : https://voiden.md/beta
1. Importing a GraphQL Schema File
You can import a GraphQL schema file such as .graphql or .gql directly into Voiden.
When you do this:
- Voiden reads all types, queries, mutations, and subscriptions from the schema
- The schema becomes available locally and works well in offline scenarios
- You get a stable, version-controlled setup that aligns nicely with Git workflows
This approach is ideal when you already have the schema file and want full control over it.
2. Using GraphQL Introspection
Alternatively, you can provide a GraphQL endpoint URL to Voiden.
In this case :
- Voiden make an introspection query to the GraphQL server
- The server returns all available types, queries, mutations, and subscriptions
- Voiden automatically loads this information so you can start querying immediately
This option is perfect for quickly exploring a live GraphQL API or when the schema file is not available locally.
Use GraphQL in our beta version : https://voiden.md/beta
reacted to
sequelbox's
post with 👀
3 days ago
Post
2496
NEW RELEASE: it's here! Meet the newest member of the Valiant crew: Guardpoint, our new medical reasoning model!
- Trained on medical knowledge, management, diagnosis, and tasks from DeepSeek-V3.2-Speciale!
- Structured medical reasoning responses are efficient and informative, cutting token costs for faster inference!
- Wide-ranging knowledge base: trained on a wide variety of medical disciplines, patient types, and query structures!
- High quality medical responses emphasize performance, brevity, specificity, statistical rationality, and openness.
Get it now:
Guardpoint for Qwen 3 32B: ValiantLabs/Qwen3-32B-Guardpoint
Guardpoint for Qwen 3 14B: ValiantLabs/Qwen3-14B-Guardpoint
Powered by our new structured medical reasoning dataset: sequelbox/Superpotion-DeepSeek-V3.2-Speciale
We've been working hard on Guardpoint; we're really excited to share it with everyone!
We'll be bringing Guardpoint to more models soon, along with further releases for the Shining Valiant and Esper series!
Get our experimental models: https://huggingface.co/collections/sequelbox/experimental-reasoning-models
Get our reasoning datasets: https://huggingface.co/collections/sequelbox/reasoning-datasets
Help support our releases, donations used for our experimental models and datasets: sequelbox/SupportOpenSource
2026 is going to be an amazing year for open source AI! It's time for the AI revolution you need; from the bottom up, built together by all of us.
for love, friendship, and better days,
allegra
- Trained on medical knowledge, management, diagnosis, and tasks from DeepSeek-V3.2-Speciale!
- Structured medical reasoning responses are efficient and informative, cutting token costs for faster inference!
- Wide-ranging knowledge base: trained on a wide variety of medical disciplines, patient types, and query structures!
- High quality medical responses emphasize performance, brevity, specificity, statistical rationality, and openness.
Get it now:
Guardpoint for Qwen 3 32B: ValiantLabs/Qwen3-32B-Guardpoint
Guardpoint for Qwen 3 14B: ValiantLabs/Qwen3-14B-Guardpoint
Powered by our new structured medical reasoning dataset: sequelbox/Superpotion-DeepSeek-V3.2-Speciale
We've been working hard on Guardpoint; we're really excited to share it with everyone!
We'll be bringing Guardpoint to more models soon, along with further releases for the Shining Valiant and Esper series!
Get our experimental models: https://huggingface.co/collections/sequelbox/experimental-reasoning-models
Get our reasoning datasets: https://huggingface.co/collections/sequelbox/reasoning-datasets
Help support our releases, donations used for our experimental models and datasets: sequelbox/SupportOpenSource
2026 is going to be an amazing year for open source AI! It's time for the AI revolution you need; from the bottom up, built together by all of us.
for love, friendship, and better days,
allegra
reacted to
MikeDoes's
post with 👀
3 days ago
Post
172
The future of AI privacy isn't just in the cloud; it's on your device. But how do we build and validate these tools?
A new paper on "Rescriber" explores this with a tool that uses smaller LLMs for on-device anonymization. Building and validating such tools requires a strong data foundation. We're excited to see that the researchers used the Ai4Privacy open dataset to create their performance benchmarks.
This is our mission in action: providing the open-source data that helps innovators build and test better solutions that will give users more control over their privacy. It's a win for the community when our data helps prove the feasibility of on-device AI for data minimization, with reported user perceptions on par with state-of-the-art cloud models.
Shoutout to Jijie Zhou, Eryue Xu, Yaoyao Wu, and Tianshi Li on this one!
🔗 Check out the research to see how on-device AI, powered by solid data, is changing the game: https://dl.acm.org/doi/pdf/10.1145/3706598.3713701
🚀 Stay updated on the latest in privacy-preserving AI—follow us on LinkedIn: https://www.linkedin.com/company/ai4privacy/posts/
#OpenSource
#DataPrivacy
#LLM
#Anonymization
#AIsecurity
#HuggingFace
#Ai4Privacy
#Worldslargestopensourceprivacymaskingdataset
A new paper on "Rescriber" explores this with a tool that uses smaller LLMs for on-device anonymization. Building and validating such tools requires a strong data foundation. We're excited to see that the researchers used the Ai4Privacy open dataset to create their performance benchmarks.
This is our mission in action: providing the open-source data that helps innovators build and test better solutions that will give users more control over their privacy. It's a win for the community when our data helps prove the feasibility of on-device AI for data minimization, with reported user perceptions on par with state-of-the-art cloud models.
Shoutout to Jijie Zhou, Eryue Xu, Yaoyao Wu, and Tianshi Li on this one!
🔗 Check out the research to see how on-device AI, powered by solid data, is changing the game: https://dl.acm.org/doi/pdf/10.1145/3706598.3713701
🚀 Stay updated on the latest in privacy-preserving AI—follow us on LinkedIn: https://www.linkedin.com/company/ai4privacy/posts/
#OpenSource
#DataPrivacy
#LLM
#Anonymization
#AIsecurity
#HuggingFace
#Ai4Privacy
#Worldslargestopensourceprivacymaskingdataset
reacted to
AdinaY's
post with 🚀
3 days ago
Post
250
GLM-Image from Z.ai is out 🔥
It was fully trained on Ascend Atlas 800T A2 with MindSpore, probably the first SOTA multimodal model fully trained on domestic chips 👀
zai-org/GLM-Image
✨ Hybrid Architecture: combined autoregressive + diffusion design delivers strong semantic alignment with high-fidelity details
✨ Strong performance in long, dense, and multilingual text rendering
✨ MIT licensed (VQ tokenizer & ViT weights under Apache 2.0)
✨ Now live on Hugging Face inference provider 🤗
It was fully trained on Ascend Atlas 800T A2 with MindSpore, probably the first SOTA multimodal model fully trained on domestic chips 👀
zai-org/GLM-Image
✨ Hybrid Architecture: combined autoregressive + diffusion design delivers strong semantic alignment with high-fidelity details
✨ Strong performance in long, dense, and multilingual text rendering
✨ MIT licensed (VQ tokenizer & ViT weights under Apache 2.0)
✨ Now live on Hugging Face inference provider 🤗
reacted to
Yehor's
post with 🔥
3 days ago
Post
216
A useful tool for all who works with audio datasets: https://github.com/RustedBytes/data-viewer-audio
reacted to
mmhamdy's
post with 🔥
3 days ago
Post
2916
The new DeepSeek Engram paper is super fun! It also integrates mHC, and I suspect they're probably releasing all these papers to make the V4 report of reasonable length😄
Here's a nice short summary from Gemini
Here's a nice short summary from Gemini
reacted to
their
post with 🔥🚀
3 days ago
Post
3678
I just released NovaSR, a tiny 52kb audio upsampler that can enhance 3600 seconds of muffled 16khz audio in to clearer 48khz audio in just 1 second!
NovaSR can
- Enhance TTS model quality.
- Restore poor quality datasets.
- Work on any device(just 52kb which is smaller than a 3 second audio file!)
Model: YatharthS/NovaSR
Space to try it: YatharthS/NovaSR
Github repo: https://github.com/ysharma3501/NovaSR
NovaSR can
- Enhance TTS model quality.
- Restore poor quality datasets.
- Work on any device(just 52kb which is smaller than a 3 second audio file!)
Model: YatharthS/NovaSR
Space to try it: YatharthS/NovaSR
Github repo: https://github.com/ysharma3501/NovaSR
-
- 2 replies
posted
an
update
3 days ago
Post
3678
I just released NovaSR, a tiny 52kb audio upsampler that can enhance 3600 seconds of muffled 16khz audio in to clearer 48khz audio in just 1 second!
NovaSR can
- Enhance TTS model quality.
- Restore poor quality datasets.
- Work on any device(just 52kb which is smaller than a 3 second audio file!)
Model: YatharthS/NovaSR
Space to try it: YatharthS/NovaSR
Github repo: https://github.com/ysharma3501/NovaSR
NovaSR can
- Enhance TTS model quality.
- Restore poor quality datasets.
- Work on any device(just 52kb which is smaller than a 3 second audio file!)
Model: YatharthS/NovaSR
Space to try it: YatharthS/NovaSR
Github repo: https://github.com/ysharma3501/NovaSR
-
-
- 2 replies
reacted to
their
post with 👍
29 days ago
Post
3675
🤯 🤯 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
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- 4 replies
reacted to
ZennyKenny's
post with 👍
30 days ago
Post
1995
🍓 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
reacted to
rajkumarrawal's
post with 👍
30 days ago
Post
1910
" An open standardized protocol enabling communication for autonomous robots to exchange data, coordinate tasks, and collaborate in real-time environments in the age of AI ". r2r-protocol (Robot2Robot Protocol) is now officially open source! 🔓
"pip install r2r-protocol"
Whether you're a developer, researcher, or tech enthusiast, we invite you to explore, use, and contribute to the project.
🔗 Check it out here: [ https://github.com/Tech-Parivartan/r2r-protocol?tab=readme-ov-file ]
Let’s build the future together! 💡
AiParivartanResearchLab
techparivartan
Documentation of the r2r-protocal : [ https://techparivartanai.notion.site/Robot-to-Robot-r2r-Protocol-1f008f0fb18780439d70e8b9bbbdb869 ]
The R2R Protocol enables seamless robot-to-robot interaction across industrial automation, swarm robotics, logistics, and multi-agent systems. It defines structured message formats, negotiation logic, discovery mechanisms, and extensible APIs.
#r2r_protocol #robot2robot_protocol #ai #aiparivartanresearchlab #techparivartan
https://huggingface.co/blog/rajkumarrawal/rawalraj
"pip install r2r-protocol"
Whether you're a developer, researcher, or tech enthusiast, we invite you to explore, use, and contribute to the project.
🔗 Check it out here: [ https://github.com/Tech-Parivartan/r2r-protocol?tab=readme-ov-file ]
Let’s build the future together! 💡
Documentation of the r2r-protocal : [ https://techparivartanai.notion.site/Robot-to-Robot-r2r-Protocol-1f008f0fb18780439d70e8b9bbbdb869 ]
The R2R Protocol enables seamless robot-to-robot interaction across industrial automation, swarm robotics, logistics, and multi-agent systems. It defines structured message formats, negotiation logic, discovery mechanisms, and extensible APIs.
#r2r_protocol #robot2robot_protocol #ai #aiparivartanresearchlab #techparivartan
https://huggingface.co/blog/rajkumarrawal/rawalraj
reacted to
sergiopaniego's
post with 🚀
30 days ago
Post
1877
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
victor's
post with 🔥
30 days ago
Post
3114
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
Nymbo's
post with 🔥
30 days ago
Post
2118
🚨 New tool for the
Nymbo/Tools MCP server: The new
How it works: The tool exposes the standard discover/info/resources/validate actions. Skills live in
I've included a
Caveat: On HF Spaces,
Try it out ~ https://www.nymbo.net/nymbot
Agent_Skills tool provides full support for Agent Skills (Claude Skills but open-source).How it works: The tool exposes the standard discover/info/resources/validate actions. Skills live in
/Skills under the same File_System root, and any bundled scripts run through Shell_Command, no new infrastructure required.Agent_Skills(action="discover") # List all available skills
Agent_Skills(action="info", skill_name="music-downloader") # Full SKILL.md
Agent_Skills(action="resources", skill_name="music-downloader") # Scripts, refs, assetsI've included a
music-downloader skill as a working demo, it wraps yt-dlp for YouTube/SoundCloud audio extraction.Caveat: On HF Spaces,
Shell_Command works for most tasks, but some operations (like YouTube downloads) are restricted due to the container environment. For full functionality, run the server locally on your machine.Try it out ~ https://www.nymbo.net/nymbot
replied to
their
post
about 1 month ago
Sorry for the sparse info, I'll add detail later. and Yes it supports voice cloning, just change "reference_file" with your wav/mp3 file path.
reacted to
their
post with 🚀🔥
about 1 month ago
Post
3675
🤯 🤯 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
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- 4 replies