WizardCoder-15B-1.0-GGML

Maintainer: TheBloke

Total Score

115

Last updated 5/28/2024

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PropertyValue
Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model overview

The WizardCoder-15B-1.0-GGML is a large language model created by TheBloke, an AI model maintainer and contributor to open-source projects. This model is an extension of the WizardLM series, offering increased scale and performance. Compared to similar large language models like WizardLM-7B-GGML, the WizardCoder-15B-1.0-GGML model has been trained on a broader dataset and features additional capabilities for code generation and programming tasks.

Model inputs and outputs

The WizardCoder-15B-1.0-GGML model accepts natural language text as input and generates coherent, contextual responses. It can handle a wide range of tasks, from open-ended dialogue to specialized prompts for creative writing, analysis, and more.

Inputs

  • Natural language text prompts
  • Multi-turn conversational exchanges

Outputs

  • Relevant, contextual text responses
  • Code snippets and solutions for programming tasks
  • Summaries, analyses, and task-oriented outputs

Capabilities

The WizardCoder-15B-1.0-GGML model has been trained to excel at text generation, code generation, and language understanding. It can engage in natural conversations, answer questions, write creative stories, and provide solutions to coding problems. The model's large scale and specialized training allow it to produce high-quality, coherent outputs across a diverse range of use cases.

What can I use it for?

The WizardCoder-15B-1.0-GGML model is well-suited for a variety of applications, including:

  • Chatbots and virtual assistants
  • Creative writing and story generation
  • Code generation and programming assistance
  • Content creation and summarization
  • Language understanding and analysis

Users can leverage the model's capabilities to build AI-powered applications, enhance productivity, and explore the boundaries of language-based AI.

Things to try

One interesting aspect of the WizardCoder-15B-1.0-GGML model is its ability to generate coherent and relevant code snippets in response to natural language prompts. You can try providing the model with programming-related prompts, such as "Write a Python function to calculate the Fibonacci sequence up to a given number," and observe the model's ability to produce working code solutions. Additionally, you can experiment with prompts that combine language tasks and coding, such as "Explain the concept of object-oriented programming in a paragraph, and then provide an example implementation in Java."



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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