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Varun reddy

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GITAM • 1y

Fine-Tuning: The Secret Sauce of AI Magic! Ever wonder how AI gets so smart? It’s all about fine-tuning! Imagine a pre-trained model as a genius with general knowledge. 🧠✨ Fine-tuning takes that genius and hones its skills for a specific task, li

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Nikhil Raj Singh

Entrepreneur | Build... • 28d

Hiring AI/ML Engineer 🚀 Join us to shape the future of AI. Work hands-on with LLMs, transformers, and cutting-edge architectures. Drive breakthroughs in model training, fine-tuning, and deployment that directly influence product and research outcom

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Kimiko

Startups | AI | info... • 4m

X updates its developer agreement to ban third parties from using the X API or X Content for training or fine-tuning foundation or frontier AI models.

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Dhruv Pithadia

A.I. Enthusiast • 6m

Working on a cool AI project, that involves vector db and LLM fine-tuning

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AI Engineer

AI Deep Explorer | f... • 6m

"A Survey on Post-Training of Large Language Models" This paper systematically categorizes post-training into five major paradigms: 1. Fine-Tuning 2. Alignment 3. Reasoning Enhancement 4. Efficiency Optimization 5. Integration & Adaptation 1️⃣ Fin

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Aditya Karnam

Hey I am on Medial • 6m

"Just fine-tuned LLaMA 3.2 using Apple's MLX framework and it was a breeze! The speed and simplicity were unmatched. Here's the LoRA command I used to kick off training: ``` python lora.py \ --train \ --model 'mistralai/Mistral-7B-Instruct-v0.2' \ -

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Account Deleted

Hey I am on Medial • 8m

Another open-source model has arrived, and it’s even better than DeepSeek-V3. The Allen Institute for AI just introduced Tülu 3 (405B) 🐫, a post-training model that is a fine-tune of Llama 3.1 405B, which outperforms DeepSeek V3.

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Comet

#freelancer • 10m

10 Best LLM Tools to Simplify Your Workflow 1️⃣ LangChain LangChain's flexibility suits complex AI and multi-stage processing. 2️⃣ Cohere Cohere offers integration, scalability, and customization. 3️⃣ Falcon Falcon offers cost-effective, high-per

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Jainil Prajapati

Turning dreams into ... • 7m

India should focus on fine-tuning existing AI models and building applications rather than investing heavily in foundational models or AI chips, says Groq CEO Jonathan Ross. Is this the right strategy for India to lead in AI innovation? Thoughts?

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