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I share my GitHub because I want you to go beyond paper reading and actually implement the DeepSeek R1 / R1-Zero ideas in code. If you’re building agents, RAG, or evaluation scripts, having a working reference saves you hours and keeps your experiments reproducible.

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Pros

  • +Hands-on reference code to speed up implementation
  • +Easy to adapt for your own experiments

Cons

  • -May require you to adjust dependencies for your setup
  • -Not a one-click solution for every environment

Featured in 13 videos

The DeepSeek OCR Paper [Explained] AI Can Now See Text Instead of Reading | Optical Compression

The DeepSeek OCR Paper [Explained] AI Can Now See Text Instead of Reading | Optical Compression

748 views · 2025-11-17 05:30:01

Build 9 End-to-End GenAI Projects before 2025 [ RAG + Agentic AI + LLMs ] Scalable System Design

Build 9 End-to-End GenAI Projects before 2025 [ RAG + Agentic AI + LLMs ] Scalable System Design

41K views · 2025-10-30 12:30:27

GenAI Roadmap [Ultimate AI Roadmap] 2025 | From GenAI LLMs RAG Agentic AI | Future Ready Guide

GenAI Roadmap [Ultimate AI Roadmap] 2025 | From GenAI LLMs RAG Agentic AI | Future Ready Guide

3K views · 2025-10-28 12:30:09

Design Spotify Recommendation Engine | How Music Recommenders Work? Scalable System Design

Design Spotify Recommendation Engine | How Music Recommenders Work? Scalable System Design

1K views · 2025-10-12 15:30:34

Squid Game X AI [Red Light, Green Light] | Machine Learning System Design + Computer Vision

Squid Game X AI [Red Light, Green Light] | Machine Learning System Design + Computer Vision

754 views · 2025-09-09 18:00:34

TCS to Google | From Manual Tester to Machine Learning Engineer | Punjab to FAANG | Tier 3 to GenAI

TCS to Google | From Manual Tester to Machine Learning Engineer | Punjab to FAANG | Tier 3 to GenAI

85K views · 2025-08-31 05:30:03

Netflix ML System Design [Explained] Video Recommendation System | Retriever Ranker Models

Netflix ML System Design [Explained] Video Recommendation System | Retriever Ranker Models

2K views · 2025-08-23 05:30:00

OpenAI Agents SDK [Explained] Build OpenAI Research Assistant Step-by-Step using Python

OpenAI Agents SDK [Explained] Build OpenAI Research Assistant Step-by-Step using Python

734 views · 2025-06-02 12:30:07

Will KAG surpassed RAG? KAG [Knowledge Augmented Generation] Architecture and Working Explained

Will KAG surpassed RAG? KAG [Knowledge Augmented Generation] Architecture and Working Explained

2K views · 2025-03-05 12:30:16

How to Distill LLM? LLM Distilling [Explained] Step-by-Step using Python Hugging Face AutoTrain

How to Distill LLM? LLM Distilling [Explained] Step-by-Step using Python Hugging Face AutoTrain

7K views · 2025-02-28 09:30:25

Deepseek R1 Fine Tuning [ How to Fine Tune LLM ] Parameter Efficient Fine Tuning LORA Unsloth Ollama

Deepseek R1 Fine Tuning [ How to Fine Tune LLM ] Parameter Efficient Fine Tuning LORA Unsloth Ollama

18K views · 2025-02-12 12:30:23

DeepSeek R1 vs Google Gemini [Comparison] Ollama FAISS VectorDB RAG Streamlit GenAI Project Tutorial

DeepSeek R1 vs Google Gemini [Comparison] Ollama FAISS VectorDB RAG Streamlit GenAI Project Tutorial

1K views · 2025-02-08 12:30:16

DeepSeek R1 vs DeepSeek R1 Zero [Architecture Explained] | Run DeepSeek R1 Locally with Ollama

DeepSeek R1 vs DeepSeek R1 Zero [Architecture Explained] | Run DeepSeek R1 Locally with Ollama

592 views · 2025-02-05 23:15:05