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Goekdeniz-Guelmez  authored a paper about 1 month ago
Gabliteration: Adaptive Multi-Directional Neural Weight Modification for Selective Behavioral Alteration in Large Language Models
1024m  authored a paper 6 months ago
Query Attribute Modeling: Improving search relevance with Semantic Search and Meta Data Filtering
1024m  authored a paper 6 months ago
DSBC : Data Science task Benchmarking with Context engineering
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Parveshiiii 
posted an update about 1 hour ago
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🚀 Wanna train your own AI Model or Tokenizer from scratch?

Building models isn’t just for big labs anymore — with the right data, compute, and workflow, you can create **custom AI models** and **tokenizers** tailored to any domain. Whether it’s NLP, domain‑specific datasets, or experimental architectures, training from scratch gives you full control over vocabulary, embeddings, and performance.

✨ Why train your own?
- Full control over vocabulary & tokenization
- Domain‑specific optimization (medical, legal, technical, etc.)
- Better performance on niche datasets
- Freedom to experiment with architectures

⚡ The best part?
- Tokenizer training (TikToken / BPE) can be done in **just 3 lines of code**.
- Model training runs smoothly on **Google Colab notebooks** — no expensive hardware required.

📂 Try out my work:
- 🔗 https://github.com/OE-Void/Tokenizer-from_scratch
- 🔗 https://github.com/OE-Void/GPT
Parveshiiii 
posted an update 5 days ago
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📢 The Announcement
Subject: XenArcAI is now Modotte – A New Chapter Begins! 🚀

Hello everyone,

We are thrilled to announce that XenArcAI is officially rebranding to Modotte!

Since our journey began, we’ve been committed to pushing the boundaries of AI through open-source innovation, research, and high-quality datasets. As we continue to evolve, we wanted a name that better represents our vision for a modern, interconnected future in the tech space.

What is changing?

The Name: Moving forward, all our projects, models, and community interactions will happen under the Modotte banner.

The Look: You’ll see our new logo and a fresh color palette appearing across our platforms.

What is staying the same?

The Core Team: It’s still the same people behind the scenes, including our founder, Parvesh Rawal.

Our Mission: We remain dedicated to releasing state-of-the-art open-source models and datasets.

Our Continuity: All existing models, datasets, and projects will remain exactly as they are—just with a new home.

This isn’t just a change in appearance; it’s a commitment to our next chapter of growth and discovery. We are so grateful for your ongoing support as we step into this new era.

Welcome to the future. Welcome to Modotte.

Best regards, The Modotte Team
Goekdeniz-Guelmez 
authored a paper about 1 month ago
Parveshiiii 
posted an update about 1 month ago
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Hey everyone!
We’re excited to introduce our new Telegram group: https://t.me/XenArcAI

This space is built for **model builders, tech enthusiasts, and developers** who want to learn, share, and grow together. Whether you’re just starting out or already deep into AI/ML, you’ll find a supportive community ready to help with knowledge, ideas, and collaboration.

💡 Join us to:
- Connect with fellow developers and AI enthusiasts
- Share your projects, insights, and questions
- Learn from others and contribute to a growing knowledge base

👉 If you’re interested, hop in and be part of the conversation: https://t.me/XenArcAI
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Parveshiiii 
posted an update 2 months ago
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Another banger from XenArcAI! 🔥

We’re thrilled to unveil three powerful new releases that push the boundaries of AI research and development:

🔗 https://huggingface.co/XenArcAI/SparkEmbedding-300m

- A lightning-fast embedding model built for scale.
- Optimized for semantic search, clustering, and representation learning.

🔗 https://huggingface.co/datasets/XenArcAI/CodeX-7M-Non-Thinking

- A massive dataset of 7 million code samples.
- Designed for training models on raw coding patterns without reasoning layers.

🔗 https://huggingface.co/datasets/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 3 months ago
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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: https://huggingface.co/XenArcAI/SparkEmbedding-300m
Parveshiiii 
posted an update 3 months ago
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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: https://huggingface.co/XenArcAI/AIRealNet
Parveshiiii 
posted an update 4 months ago
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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
Parveshiiii 
posted an update 4 months ago
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🚀 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: https://huggingface.co/datasets/XenArcAI/Bhagwat-Gita-Infinity

Let’s bring timeless wisdom into modern AI together 🙌
Parveshiiii 
posted an update 4 months ago
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🚀 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:
👉 https://huggingface.co/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.
Abhaykoul 
posted an update 5 months ago
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🚀 Ever dreamed of training your own Large Language Model from scratch? What if I told you it doesn't require a supercomputer or PhD in ML? 🤯

Introducing LLM Trainer - the educational framework that makes LLM training accessible to EVERYONE! Whether you're on a CPU-only laptop or scaling to distributed GPUs, we've got you covered. 💻➡️🖥️

Why LLM Trainer? Because existing tools are either too simplistic (hiding the magic) or too complex (requiring expert knowledge). We bridge the gap with:

🎓 Educational transparency - every component built from scratch with clear code
💻 CPU-first approach - start training immediately, no GPU needed
🔧 Full customization - modify anything you want
📈 Seamless scaling - from laptop to cluster without code changes
🤝 HuggingFace integration - works with existing models & tokenizers

Key highlights:
✅ Built-in tokenizers (BPE, WordPiece, HF wrappers)
✅ Complete Transformer implementation from scratch
✅ Optimized for CPU training
✅ Advanced features: mixed precision, gradient checkpointing, multiple generation strategies
✅ Comprehensive monitoring & metrics

Perfect for:
- Students learning transformers
- Researchers prototyping new ideas
- Developers building domain-specific models

Ready to train your first LLM? It's easier than you think!

🔗 Check it out: https://github.com/HelpingAI/llm-trainer
📚 Docs: Getting Started Guide
💬 Join the community: GitHub Discussions

#AI #MachineLearning #LLM #DeepLearning #OpenSource #Python #HuggingFace #NLP

Special thanks to HuggingFace and PyTorch teams for the amazing ecosystem! 🙏
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1024m 
authored a paper 6 months ago
Parveshiiii 
posted an update 6 months ago
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🚀 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**](https://huggingface.co/datasets/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 , , and formats
- 🧮 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: (https://huggingface.co/datasets/XenArcAI/MathX-5M)

Let’s make open-source models *actually* smart at math.
#FineTuneYourGPT #MathX5M #OpenSourceAI #LLM #XenArcAI #Reasoning #Gemma #Qwen #Mistral
1024m 
authored a paper 6 months ago
alielfilali01 
posted an update 6 months ago
Abhaykoul 
posted an update 6 months ago
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🚀 Dhanishtha-2.0-preview-0825 Is Here

The Intermediate Thinking Model just leveled up again.

With sharper reasoning, better tool use, and expanded capabilities, Dhanishtha-2.0-preview-0825 is now live and ready to impress.

🧠 What Makes Dhanishtha Special?
Unlike typical CoT models that only thinks one time, Dhanishtha thinks iteratively:

> Think → Answer → Rethink → Improve → Rethink again if needed.

🔗 Try it now: HelpingAI/Dhanishtha-2.0-preview-0825

🔞 Dhanishtha NSFW Preview

For those exploring more expressive and immersive roleplay scenarios, we’re also releasing:

HelpingAI/Dhanishtha-nsfw
A specialized version tuned for adult-themed interactions and character-driven roleplay.

🔗 Explore it here: HelpingAI/Dhanishtha-nsfw

💬 You can also try all of these live at chat.helpingai.co
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Parveshiiii 
posted an update 6 months ago
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🚀 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.

+ 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
erikkaum 
posted an update 6 months ago
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ZML just released a technical preview of their new Inference Engine: LLMD.

- Just 2.4GB container, which means fast startup times and efficient autoscaling
- Cross-Platform GPU Support: works on both NVIDIA and AMD GPUs.
- written in Zig

I just tried it out and deployed it on Hugging Face Inference Endpoints and wrote a quick guide 👇 You can try it in like 5 minutes!

https://huggingface.co/blog/erikkaum/test-driving-llmd-inference-engine
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erikkaum 
posted an update 6 months ago
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We just released native support for @SGLang and @vllm-project in Inference Endpoints 🔥

Inference Endpoints is becoming the central place where you deploy high performance Inference Engines.

And that provides the managed infra for it. Instead of spending weeks configuring infrastructure, managing servers, and debugging deployment issues, you can focus on what matters most: your AI model and your users 🙌
Abhaykoul 
posted an update 6 months ago
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🎉 Dhanishtha-2.0-preview-0725 is Now Live

The Intermediate Thinking Model just got even better.
With the new update, Dhanishtha is now sharper, smarter, and trained further on tool use

🧠 What Makes Dhanishtha Different?
Unlike standard COT models that give one-shot responses, Dhanishtha thinks in layers:

> Think → Answer → Rethink → Improve → Rethink again if needed.

HelpingAI/Dhanishtha-2.0-preview-0725