anime datasets \(￣︶￣*\))
Collection
this is a collection of anime datasets
•
12 items
•
Updated
AI & ML interests
LowRes animated waifus (✿◡‿◡)
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potato4code
updated
a
collection
10 days ago
Parveshiiii
posted
an
update
20 days ago
Post
1603
Another banger from XenArcAI! 🔥
We’re thrilled to unveil three powerful new releases that push the boundaries of AI research and development:
🔗 XenArcAI/SparkEmbedding-300m
- A lightning-fast embedding model built for scale.
- Optimized for semantic search, clustering, and representation learning.
🔗 XenArcAI/CodeX-7M-Non-Thinking
- A massive dataset of 7 million code samples.
- Designed for training models on raw coding patterns without reasoning layers.
🔗 XenArcAI/CodeX-2M-Thinking
- A curated dataset of 2 million code samples.
- Focused on reasoning-driven coding tasks, enabling smarter AI coding assistants.
Together, these projects represent a leap forward in building smarter, faster, and more capable AI systems.
💡 Innovation meets dedication.
🌍 Knowledge meets responsibility.
We’re thrilled to unveil three powerful new releases that push the boundaries of AI research and development:
🔗 XenArcAI/SparkEmbedding-300m
- A lightning-fast embedding model built for scale.
- Optimized for semantic search, clustering, and representation learning.
🔗 XenArcAI/CodeX-7M-Non-Thinking
- A massive dataset of 7 million code samples.
- Designed for training models on raw coding patterns without reasoning layers.
🔗 XenArcAI/CodeX-2M-Thinking
- A curated dataset of 2 million code samples.
- Focused on reasoning-driven coding tasks, enabling smarter AI coding assistants.
Together, these projects represent a leap forward in building smarter, faster, and more capable AI systems.
💡 Innovation meets dedication.
🌍 Knowledge meets responsibility.
Parveshiiii
posted
an
update
27 days ago
Post
3016
SparkEmbedding - SoTA cross lingual retrieval
Iam very happy to announce our latest embedding model sparkembedding-300m base on embeddinggemma-300m we fine tuned it on 1m extra examples spanning over 119 languages and result is this model achieves exceptional cross lingual retrieval
Model: XenArcAI/SparkEmbedding-300m
Iam very happy to announce our latest embedding model sparkembedding-300m base on embeddinggemma-300m we fine tuned it on 1m extra examples spanning over 119 languages and result is this model achieves exceptional cross lingual retrieval
Model: XenArcAI/SparkEmbedding-300m
Post
534
Eduhelp with more empathy, based on model finetuned on
psychotheraputic preferences just landed on
Beck-8B as a base model, 13000 steps on educational dataset.
Time to go further and build more 🥰
s3nh/EduHelp_Beck_8B
Thanks to @basilic_ai for computations <3
psychotheraputic preferences just landed on
Beck-8B as a base model, 13000 steps on educational dataset.
Time to go further and build more 🥰
s3nh/EduHelp_Beck_8B
Thanks to @basilic_ai for computations <3
Parveshiiii
posted
an
update
about 2 months ago
Post
196
AIRealNet - SoTA - Image detection model
We’re proud to release AIRealNet — a binary image classifier built to detect whether an image is AI-generated or a real human photograph. Based on SwinV2 and fine-tuned on the AI-vs-Real dataset, this model is optimized for high-accuracy classification across diverse visual domains.
If you care about synthetic media detection or want to explore the frontier of AI vs human realism, we’d love your support. Please like the model and try it out. Every download helps us improve and expand future versions.
Model page: XenArcAI/AIRealNet
We’re proud to release AIRealNet — a binary image classifier built to detect whether an image is AI-generated or a real human photograph. Based on SwinV2 and fine-tuned on the AI-vs-Real dataset, this model is optimized for high-accuracy classification across diverse visual domains.
If you care about synthetic media detection or want to explore the frontier of AI vs human realism, we’d love your support. Please like the model and try it out. Every download helps us improve and expand future versions.
Model page: XenArcAI/AIRealNet
Post
4104
Just tried to create an educational assistant for younger people who can struggle with visualsation of 'what is this sorcery all about'.
Its first step of my spare time projects, sft on Qwen3-8B,
EduHelper is a child-friendly tutoring assistant fine-tuned from the Qwen3-8B base model using parameter-efficient fine-tuning (PEFT) with LoRA on the ajibawa-2023/Education-Young-Children dataset.
s3nh/EduHelp-8B
Glad to share my work, have a wonderful day!
Its first step of my spare time projects, sft on Qwen3-8B,
EduHelper is a child-friendly tutoring assistant fine-tuned from the Qwen3-8B base model using parameter-efficient fine-tuning (PEFT) with LoRA on the ajibawa-2023/Education-Young-Children dataset.
s3nh/EduHelp-8B
Glad to share my work, have a wonderful day!
- 2 replies
Parveshiiii
posted
an
update
2 months ago
Post
4482
Ever wanted an open‑source deep research agent? Meet Deepresearch‑Agent 🔍🤖
1. Multi‑step reasoning: Reflects between steps, fills gaps, iterates until evidence is solid.
2. Research‑augmented: Generates queries, searches, synthesizes, and cites sources.
3. Fullstack + LLM‑friendly: React/Tailwind frontend, LangGraph/FastAPI backend; works with OpenAI/Gemini.
🔗 GitHub: https://github.com/Parveshiiii/Deepresearch-Agent
1. Multi‑step reasoning: Reflects between steps, fills gaps, iterates until evidence is solid.
2. Research‑augmented: Generates queries, searches, synthesizes, and cites sources.
3. Fullstack + LLM‑friendly: React/Tailwind frontend, LangGraph/FastAPI backend; works with OpenAI/Gemini.
🔗 GitHub: https://github.com/Parveshiiii/Deepresearch-Agent
Parveshiiii
posted
an
update
2 months ago
Post
3099
🚀 Big news from XenArcAI!
We’ve just released our new dataset: **Bhagwat‑Gita‑Infinity** 🌸📖
✨ What’s inside:
- Verse‑aligned Sanskrit, Hindi, and English
- Clean, structured, and ready for ML/AI projects
- Perfect for research, education, and open‑source exploration
🔗 Hugging Face: XenArcAI/Bhagwat-Gita-Infinity
Let’s bring timeless wisdom into modern AI together 🙌
We’ve just released our new dataset: **Bhagwat‑Gita‑Infinity** 🌸📖
✨ What’s inside:
- Verse‑aligned Sanskrit, Hindi, and English
- Clean, structured, and ready for ML/AI projects
- Perfect for research, education, and open‑source exploration
🔗 Hugging Face: XenArcAI/Bhagwat-Gita-Infinity
Let’s bring timeless wisdom into modern AI together 🙌
Parveshiiii
posted
an
update
2 months ago
Post
2451
🚀 New Release from XenArcAI
We’re excited to introduce AIRealNet — our SwinV2‑based image classifier built to distinguish between artificial and real images.
✨ Highlights:
- Backbone: SwinV2
- Input size: 256×256
- Labels: artificial vs. real
- Performance: Accuracy 0.999 | F1 0.999 | Val Loss 0.0063
This model is now live on Hugging Face:
👉 XenArcAI/AIRealNet
We built AIRealNet to push forward open‑source tools for authenticity detection, and we can’t wait to see how the community uses it.
We’re excited to introduce AIRealNet — our SwinV2‑based image classifier built to distinguish between artificial and real images.
✨ Highlights:
- Backbone: SwinV2
- Input size: 256×256
- Labels: artificial vs. real
- Performance: Accuracy 0.999 | F1 0.999 | Val Loss 0.0063
This model is now live on Hugging Face:
👉 XenArcAI/AIRealNet
We built AIRealNet to push forward open‑source tools for authenticity detection, and we can’t wait to see how the community uses it.
innovation64
authored
a
paper
3 months ago
louisbrulenaudet
posted
an
update
3 months ago
Post
6172
Supercharge Apple’s Shortcuts using Cloudflare Workers and Gemini within minutes (and for free, up to 1,500 requests per day) ☁️✨
Hello everyone, last week, while experimenting for fun, I created an API that allows you to easily access AI models (in this case, Google's) from the Shortcut app in order to analyze data from my apps and make the most of it thanks to the generative capabilities of advanced models.
It costs me nothing, and I think it might be good to share it so that others can build on it.
In README.md, you will find everything you need to get started and put your own microservice into production, which you can call from the app’s HTTP request features.
You will simply be asked to have a free Cloudflare account and an API key obtained from Google's AI Studio.
Feel free to take a look and get back to me if you encounter any problems during deployment.
Here is the GitHub repo where you can find all the source code and run it on your own: https://github.com/louisbrulenaudet/genai-api
Hello everyone, last week, while experimenting for fun, I created an API that allows you to easily access AI models (in this case, Google's) from the Shortcut app in order to analyze data from my apps and make the most of it thanks to the generative capabilities of advanced models.
It costs me nothing, and I think it might be good to share it so that others can build on it.
In README.md, you will find everything you need to get started and put your own microservice into production, which you can call from the app’s HTTP request features.
You will simply be asked to have a free Cloudflare account and an API key obtained from Google's AI Studio.
Feel free to take a look and get back to me if you encounter any problems during deployment.
Here is the GitHub repo where you can find all the source code and run it on your own: https://github.com/louisbrulenaudet/genai-api
louisbrulenaudet
posted
an
update
3 months ago
Post
658
Although more and more code editors are aligning themselves with the AGENTS.md file standard, some still use specific nomenclatures that can make it difficult to maintain different configuration files when several people are working on the same project with different agents.
Bodyboard addresses this by generating canonical instructions for code helpers from a single AGENTS.md file, thereby streamlining the production of adapter outputs for Gemini CLI, Copilot, Cline, Claude, Rules, Windsurf, and OpenAI Codex integrations.
You just have to:
Then run, at the root of your project:
Link to npm: https://www.npmjs.com/package/bodyboard
Link to the GitHub repo: https://github.com/louisbrulenaudet/bodyboard
It's a very simple project, but it addresses certain issues I've encountered, so why not make it available to everyone...
If you have other ideas for adapters to create, feel free to open a PR on the GitHub repo.
Bodyboard addresses this by generating canonical instructions for code helpers from a single AGENTS.md file, thereby streamlining the production of adapter outputs for Gemini CLI, Copilot, Cline, Claude, Rules, Windsurf, and OpenAI Codex integrations.
You just have to:
npm install -g bodyboardThen run, at the root of your project:
bodyboard allLink to npm: https://www.npmjs.com/package/bodyboard
Link to the GitHub repo: https://github.com/louisbrulenaudet/bodyboard
It's a very simple project, but it addresses certain issues I've encountered, so why not make it available to everyone...
If you have other ideas for adapters to create, feel free to open a PR on the GitHub repo.
Parveshiiii
posted
an
update
4 months ago
Post
1110
🚀 Just Dropped: MathX-5M — Your Gateway to Math-Savvy GPTs
👨🔬 Wanna fine-tune your own GPT for math?
🧠 Building a reasoning agent that actually *thinks*?
📊 Benchmarking multi-step logic across domains?
Say hello to [**MathX-5M**]( XenArcAI/MathX-5M) — a **5 million+ sample** dataset crafted for training and evaluating math reasoning models at scale.
Built by **XenArcAI**, it’s optimized for:
- 🔍 Step-by-step reasoning with
- 🧮 Coverage from arithmetic to advanced algebra and geometry
- 🧰 Plug-and-play with Gemma, Qwen, Mistral, and other open LLMs
- 🧵 Compatible with Harmony, Alpaca, and OpenChat-style instruction formats
Whether you're prototyping a math tutor, testing agentic workflows, or just want your GPT to solve equations like a pro—**MathX-5M is your launchpad**.
🔗 Dive in: ( XenArcAI/MathX-5M)
Let’s make open-source models *actually* smart at math.
#FineTuneYourGPT #MathX5M #OpenSourceAI #LLM #XenArcAI #Reasoning #Gemma #Qwen #Mistral
👨🔬 Wanna fine-tune your own GPT for math?
🧠 Building a reasoning agent that actually *thinks*?
📊 Benchmarking multi-step logic across domains?
Say hello to [**MathX-5M**]( XenArcAI/MathX-5M) — a **5 million+ sample** dataset crafted for training and evaluating math reasoning models at scale.
Built by **XenArcAI**, it’s optimized for:
- 🔍 Step-by-step reasoning with
- 🧮 Coverage from arithmetic to advanced algebra and geometry
- 🧰 Plug-and-play with Gemma, Qwen, Mistral, and other open LLMs
- 🧵 Compatible with Harmony, Alpaca, and OpenChat-style instruction formats
Whether you're prototyping a math tutor, testing agentic workflows, or just want your GPT to solve equations like a pro—**MathX-5M is your launchpad**.
🔗 Dive in: ( XenArcAI/MathX-5M)
Let’s make open-source models *actually* smart at math.
#FineTuneYourGPT #MathX5M #OpenSourceAI #LLM #XenArcAI #Reasoning #Gemma #Qwen #Mistral
Parveshiiii
posted
an
update
4 months ago
Post
1096
🚀 Launch Alert: Dev-Stack-Agents
Meet your 50-agent senior AI team — principal-level experts in engineering, AI, DevOps, security, product, and more — all bundled into one modular repo.
🔧 Built for Claude Code
Seamlessly plug into Claude’s dev environment:
* 🧠 Each
* ⚙️ Claude indexes them as agents with roles, skills & strategy
* 🤖 You chat → Claude auto-routes to the right agent(s)
* ✍️ Want precision? Just call
* 👥 Complex task? Mention multiple agents for team execution
Examples:
🔗 https://github.com/Parveshiiii/Dev-Stack-Agents
MIT License | Claude-Ready | PRs Welcome
Meet your 50-agent senior AI team — principal-level experts in engineering, AI, DevOps, security, product, and more — all bundled into one modular repo.
+ Code. Optimize. Scale. Secure.
- Full-stack execution, Claude-powered. No human bottlenecks.🔧 Built for Claude Code
Seamlessly plug into Claude’s dev environment:
* 🧠 Each
.md file = a fully defined expert persona* ⚙️ Claude indexes them as agents with roles, skills & strategy
* 🤖 You chat → Claude auto-routes to the right agent(s)
* ✍️ Want precision? Just call
@agent-name directly* 👥 Complex task? Mention multiple agents for team execution
Examples:
"@security-auditor please review auth flow for risks"
"@cloud-architect + @devops-troubleshooter → design a resilient multi-region setup"
"@ai-engineer + @legal-advisor → build a privacy-safe RAG pipeline"🔗 https://github.com/Parveshiiii/Dev-Stack-Agents
MIT License | Claude-Ready | PRs Welcome
pepper13
updated
a
collection
4 months ago
Post
562
Qwen 3 Coder is a personal attack to k2, and I love it.
It achieves near SOTA on LCB while not having reasoning.
Finally people are understanding that reasoning isnt necessary for high benches...
Qwen ftw!
DECENTRALIZE DECENTRALIZE DECENTRALIZE
It achieves near SOTA on LCB while not having reasoning.
Finally people are understanding that reasoning isnt necessary for high benches...
Qwen ftw!
DECENTRALIZE DECENTRALIZE DECENTRALIZE
louisbrulenaudet
posted
an
update
5 months ago
Post
2851
Because hackathons are often the starting point for many AI projects, I've created a Python-backend template incorporating my feedback to streamline collaboration and urgent deployments 🏎️
Within a year, I had the opportunity to participate in hackathons organized by Mistral, OpenAI, and DeepMind and this GitHub template is structured around several fundamental building blocks and recommendations I offer developers eager to participate in their first hackathon, whether as part of a team or individually. Its emphasis is on rapid setup and deployment through:
- uv as a package manager, simplifying usage via a series of pre-configured make commands.
- FastAPI for API management, structured in a modular architecture designed to minimize branch conflicts during merges to main branches (using minimal health-check and ping routes to verify Docker’s proper execution and backend accessibility on the local network).
- Pydantic for validation and type handling, which simplifies debugging and enhances understanding of data objects.
- A set of custom instructions tailored for agents (Cline and GitHub Copilot), aimed at improving overall comprehension of the application and optimizing the vibe-coding experience.
This template includes unit tests with a 100% success rate and test coverage, as well as a minimal CI file ensuring that the FastAPI application runs correctly. Thus, merging code that breaks the server into production becomes impossible ⛔️
In general, I would reiterate an essential piece of advice: your two main adversaries are branch conflicts—particularly when the same file is modified concurrently within a brief period, especially if your architecture isn’t built for scalability—and deployment issues under urgent circumstances ⏱️
Link to GitHub: https://github.com/louisbrulenaudet/hackathon-backend
Simply issue these commands and you can ship your code at the speed of light:
Within a year, I had the opportunity to participate in hackathons organized by Mistral, OpenAI, and DeepMind and this GitHub template is structured around several fundamental building blocks and recommendations I offer developers eager to participate in their first hackathon, whether as part of a team or individually. Its emphasis is on rapid setup and deployment through:
- uv as a package manager, simplifying usage via a series of pre-configured make commands.
- FastAPI for API management, structured in a modular architecture designed to minimize branch conflicts during merges to main branches (using minimal health-check and ping routes to verify Docker’s proper execution and backend accessibility on the local network).
- Pydantic for validation and type handling, which simplifies debugging and enhances understanding of data objects.
- A set of custom instructions tailored for agents (Cline and GitHub Copilot), aimed at improving overall comprehension of the application and optimizing the vibe-coding experience.
This template includes unit tests with a 100% success rate and test coverage, as well as a minimal CI file ensuring that the FastAPI application runs correctly. Thus, merging code that breaks the server into production becomes impossible ⛔️
In general, I would reiterate an essential piece of advice: your two main adversaries are branch conflicts—particularly when the same file is modified concurrently within a brief period, especially if your architecture isn’t built for scalability—and deployment issues under urgent circumstances ⏱️
Link to GitHub: https://github.com/louisbrulenaudet/hackathon-backend
Simply issue these commands and you can ship your code at the speed of light:
make init
make dev
Parveshiiii
posted
an
update
5 months ago
Post
2705
🧠 Glimpses of AGI — A Vision for All Humanity
What if AGI wasn’t just a distant dream—but a blueprint already unfolding?
I’ve just published a deep dive called Glimpses of AGI, exploring how scalable intelligence, synthetic reasoning, and alignment strategies are paving a new path forward. This isn’t your average tech commentary—it’s a bold vision for conscious AI systems that reason, align, and adapt beyond narrow tasks.
🔍 Read it, upvote it if it sparks something, and let’s ignite a collective conversation about the future of AGI.
https://huggingface.co/blog/Parveshiiii/glimpses-of-agi
What if AGI wasn’t just a distant dream—but a blueprint already unfolding?
I’ve just published a deep dive called Glimpses of AGI, exploring how scalable intelligence, synthetic reasoning, and alignment strategies are paving a new path forward. This isn’t your average tech commentary—it’s a bold vision for conscious AI systems that reason, align, and adapt beyond narrow tasks.
🔍 Read it, upvote it if it sparks something, and let’s ignite a collective conversation about the future of AGI.
https://huggingface.co/blog/Parveshiiii/glimpses-of-agi
Post
4213
Hey all
Finally it's happening. DeepGit lite is back now, running on cpu only devices. Just smartly search across Github and spin up conversational agents in the background and have grounded conversation with repositories
Try it out now!!!! zamal/DeepGit
Finally it's happening. DeepGit lite is back now, running on cpu only devices. Just smartly search across Github and spin up conversational agents in the background and have grounded conversation with repositories
Try it out now!!!! zamal/DeepGit
- 1 reply
Parveshiiii
posted
an
update
5 months ago
Post
2857
🧠 MathX-5M by XenArcAI — Scalable Math Reasoning for Smarter LLMs
Introducing MathX-5M, a high-quality, instruction-tuned dataset built to supercharge mathematical reasoning in large language models. With 5 million rigorously filtered examples, it spans everything from basic arithmetic to advanced calculus—curated from public sources and enhanced with synthetic data.
🔍 Key Highlights:
- Step-by-step reasoning with verified answers
- Covers algebra, geometry, calculus, logic, and more
- RL-validated correctness and multi-stage filtering
- Ideal for fine-tuning, benchmarking, and educational AI
📂 - XenArcAI/MathX-5M
Introducing MathX-5M, a high-quality, instruction-tuned dataset built to supercharge mathematical reasoning in large language models. With 5 million rigorously filtered examples, it spans everything from basic arithmetic to advanced calculus—curated from public sources and enhanced with synthetic data.
🔍 Key Highlights:
- Step-by-step reasoning with verified answers
- Covers algebra, geometry, calculus, logic, and more
- RL-validated correctness and multi-stage filtering
- Ideal for fine-tuning, benchmarking, and educational AI
📂 - XenArcAI/MathX-5M
- 1 reply