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Build an RQA System with DeepSeek R1 using Streamlit, FAISS, and HuggingFaceEmbeddings for efficient document retrieval.
How to install and run Qwen2.5 models locally with Ollama? Leveraging its MoE architecture, 128K context length & multilingual support.
Build an efficient RAG system using DeepSeek R1 with Ollama. Explore its retrieval accuracy, reasoning & cost-effectiveness for AI.
Qwen2.5-Max rivals DeepSeek V3 with MoE architecture, 20T tokens & advanced fine-tuning. Explore its performance, benchmarks, and more.
Looking to run DeepSeek models locally on your own machine? Learn how to do it with ease using Google Colab and Ollama.
Kimi k1.5 is a Chinese AI model leveraging reinforcement learning for advanced reasoning. It excels in math, coding, and more.
DeepSeek Janus Pro 7B, a state-of-the-art multimodal AI that outperforms competitors in reasoning, text-to-image, and instruction-following.
Kimi k1.5 vs OpenAI o1: I am going to compare both the models on diverse logical and reasoning problems. Who wins - Kimi k1.5 or OpenAI o1?
Exciting ride through the evolution of DeepSeek. Discover their cost-effective approach and the possibilities of their open-source models.
Find the best performing Chinese LLM in this Kimi k1.5 Vs DeepSeek-R1 comparison. Compare the features and capabilities of both the models.
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