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Solar Pro Preview Instruct

Solar Pro Preview Instruct is an advanced large language model with 22 billion parameters, designed to operate efficiently on a single GPU. It offers superior performance compared to smaller models and rivals those significantly larger, making it a powerful tool for AI tasks.

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Solar Pro Preview Instruct is a cutting-edge large language model (LLM) developed to fit into a single GPU with 22 billion parameters. This model demonstrates exceptional performance, surpassing models with less than 30 billion parameters and competing with those over three times its size, such as Llama 3.1 with 70 billion parameters. The model is built using an enhanced version of the depth up-scaling method, scaling a Phi-3-medium model from 14 billion to 22 billion parameters, optimized for a GPU with 80GB of VRAM.

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The training strategy and dataset for Solar Pro Preview have been meticulously curated, resulting in significant performance improvements over the Phi-3-medium model, especially on benchmarks like MMLU-Pro and IFEval, which assess a model's knowledge and instruction-following capabilities. Although this is a pre-release version, it already stands out for its efficiency and capability, with plans for the official Solar Pro release in November 2024, which will include expanded language support and longer context windows.

Solar Pro Preview is specifically designed for instruction-following tasks and conversational engagements, utilizing the ChatML template for optimal performance. This model is available as an API in the Upstage Console, providing various methods for integration. Despite its current limitations in language coverage and context length, Solar Pro Preview is poised for further development and enhancement.

  • CategoryAI Models & LLMs
  • DeploymentCloud
  • PlatformsWeb

  • 22 billion parameters

  • Single GPU compatibility

  • Superior performance to models under 30B parameters

  • Comparable to models over 70B parameters

  • Enhanced depth up-scaling method

  • Optimized for 80GB VRAM

  • Instruction-tuned for conversational tasks

  • Available as API in Upstage Console

  1. Access page: Visit Hugging Face model page

  2. Load model: Use provided inference code

  3. Configure environment: Set up GPU with 80GB VRAM

  4. Integrate: Use API in Upstage Console

  5. Fine-tune: Apply ChatML template for tasks

  • Conversational AI
  • Instruction Following
  • Benchmark Testing
  • API Integration
  • Language Model Research

From Upstage

Solar Pro Preview Instruct Reviews

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