Sold by: Futuralis
AI-Driven Story Completion leverages Mistral-7B, an open-source language model, to generate high-quality and coherent text completions. Optimized with 4-bit quantization, LoRA, and gradient checkpointing, this solution enhances AI training efficiency using AWS SageMaker and Unsloth. Deployed on NVIDIA T4-powered g4dn instances, it ensures scalable and cost-effective model training for AI-driven storytelling.
Overview
AI-Driven Story Completion demonstrates the power of AI in text generation by training the Mistral-7B model on the "TinyStories" dataset to create compelling and relevant story continuations. This solution incorporates state-of-the-art optimization techniques such as 4-bit quantization, LoRA (Low-Rank Adaptation), and gradient checkpointing to reduce computational costs while maintaining high-quality outputs.
Built on AWS SageMaker and running on g4dn instances with NVIDIA T4 GPUs, the solution takes advantage of AWS’s scalable infrastructure for efficient training and inference. By integrating Unsloth, a specialized AI training framework, the process is further optimized for speed and resource efficiency.
This solution is ideal for AI developers, content creators, and organizations looking to streamline large-scale text generation and NLP tasks without incurring excessive computational costs.
Highlights
- ✅ Optimized AI Training: Utilizes 4-bit quantization, LoRA, and gradient checkpointing for memory-efficient and accelerated training. ✅ AWS-Powered Scalability: Runs on AWS SageMaker with NVIDIA T4 GPUs for cost-effective and scalable AI model deployment. ✅ Unsloth Integration: Enhances training speed and efficiency, making AI-driven storytelling accessible to a broader audience.
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Deployed on AWS
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Support description:
Futuralis provides 24/7 support for our Managed Vulnerability Management Services. Customers can reach our dedicated support team via: Email: support@futuralis.com Web Portal: https://futuralis.com/contact-us/ Our support team is committed to responding to all inquiries within 1 hour and resolving issues based on their severity level, as outlined in our Service Level Agreement