If you are beginner you should go for books for dl as there are no cources on internet those are actually useful as most of experts are earing more that what they would earn if they sell cources so I would suggest take any deep learning book and try to do practical learning. If you want video you can go for andrej karapathy yt playlist but it's not for beginner so read some books and research papers before watching ut
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Parveshiiii
AI & ML interests
I love deep neural nets.
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2 days ago
Post
3359
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
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
posted
an
update
2 days ago
Post
3359
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
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
Post
1638
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.
posted
an
update
about 1 month ago
Post
1638
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.
Post
3040
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
posted
an
update
about 1 month ago
Post
3040
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
211
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
posted
an
update
2 months ago
Post
211
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
4492
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
posted
an
update
3 months ago
Post
4492
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
Post
3108
🚀 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 🙌
posted
an
update
3 months ago
Post
3108
🚀 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 🙌
Post
2459
🚀 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.
posted
an
update
3 months ago
Post
2459
🚀 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.
Post
1113
🚀 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
, , 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: ( XenArcAI/MathX-5M)
Let’s make open-source models *actually* smart at math.
#FineTuneYourGPT #MathX5M #OpenSourceAI #LLM #XenArcAI #Reasoning #Gemma #Qwen #Mistral
posted
an
update
5 months ago
Post
1113
🚀 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
, , 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: ( XenArcAI/MathX-5M)
Let’s make open-source models *actually* smart at math.
#FineTuneYourGPT #MathX5M #OpenSourceAI #LLM #XenArcAI #Reasoning #Gemma #Qwen #Mistral
reacted to
Abhaykoul's
post with 🔥
5 months ago
Post
4145
🚀 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
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