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Sumanth

@Sumanth_077 • 76,426 subscribers

Simplifying LLMs, RAG, Machine Learning & AI Agents for you! • ML Developer Advocate • Shipping Open Source AI apps

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Pandas is a powerful data analysis and manipulation library for Python! NVIDIA just made Pandas 150x faster with zero code changes🔥 All you have to add is just a couple of lines of code: %load_ext cudf.pandas import pandas as pd

Pandas is a powerful data analysis and manipulation library for Python! NVIDIA just made Pandas 150x faster with zero code changes🔥 All you have to add is just a couple of lines of code: %load_ext cudf.pandas import pandas as pd

180,800 次观看

Learn how LLMs work under the hood! This is the best interactive website to learn how LLMs work. It combines clear, step-by-step explanations with dynamic 3D visualizations for an intuitive learning experience.

Learn how LLMs work under the hood! This is the best interactive website to learn how LLMs work. It combines clear, step-by-step explanations with dynamic 3D visualizations for an intuitive learning experience.

113,009 次观看

How LLMs work, clearly explained with visuals:

How LLMs work, clearly explained with visuals:

174,857 次观看

Videos

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DeepSeek released R1, the best open-source reasoning model that is on par with OpenAI's o1! I have built a RAG app to chat with your PDF files using the DeepSeek R1 model, running locally on your computer. 100% Open Source

DeepSeek released R1, the best open-source reasoning model that is on par with OpenAI's o1! I have built a RAG app to chat with your PDF files using the DeepSeek R1 model, running locally on your computer. 100% Open Source

678,527 次观看 • 1 年前

MetaAI's SAM 2 struggles when things move fast or when there are crowded, fast-moving objects! Introducing SAMURAI: An adaptation of the Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory. 100% Open Source

MetaAI's SAM 2 struggles when things move fast or when there are crowded, fast-moving objects! Introducing SAMURAI: An adaptation of the Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory. 100% Open Source

324,545 次观看 • 1 年前

Transformers visually explained:

Transformers visually explained:

212,013 次观看 • 1 年前

How LLMs work, clearly explained with visuals:

How LLMs work, clearly explained with visuals:

204,362 次观看 • 1 年前

Run AI Agents locally in your terminal using Llama 3.2! gptme: Run Code, edit files, browse the web, and add context with RAG - all from your terminal. 100% Open Source.

Run AI Agents locally in your terminal using Llama 3.2! gptme: Run Code, edit files, browse the web, and add context with RAG - all from your terminal. 100% Open Source.

78,860 次观看 • 1 年前

Apple just released and open-sourced FastVLM! FastVLM is a lightning-fast vision-language model that combines rapid image and text understanding with efficient on-device performance. 100% Open Source

Apple just released and open-sourced FastVLM! FastVLM is a lightning-fast vision-language model that combines rapid image and text understanding with efficient on-device performance. 100% Open Source

43,685 次观看 • 9 个月前

Open AI released Operator, an agent that can use the browser to perform and automate tasks for you! I have built an Open Source version of Operator using Browser Use, running locally on your computer. 100% Open Source

Open AI released Operator, an agent that can use the browser to perform and automate tasks for you! I have built an Open Source version of Operator using Browser Use, running locally on your computer. 100% Open Source

62,484 次观看 • 1 年前

I connected the GitHub MCP server to my terminal AI agent, analyzed the code, and generated tests, right inside my terminal! @Warpdotdev just dropped MCP support, and you can now connect external data sources to your terminal's AI agent. It’s free and super easy to set up

I connected the GitHub MCP server to my terminal AI agent, analyzed the code, and generated tests, right inside my terminal! @Warpdotdev just dropped MCP support, and you can now connect external data sources to your terminal's AI agent. It’s free and super easy to set up

14,752 次观看 • 1 年前

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