deepseek-coder-6.7B-instruct-GGUF

Maintainer: TheBloke

Total Score

162

Last updated 5/27/2024

🏷️

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 deepseek-coder-6.7B-instruct-GGUF is an AI model created by DeepSeek and maintained by TheBloke. It is a 6.7 billion parameter language model that has been fine-tuned for code generation and understanding. The model files have been quantized to the GGUF format, which offers advantages over the previous GGML format. Similar models available include the Phind-CodeLlama-34B-v2-GGUF and the Llama-2-7B-Chat-GGUF, all of which have been quantized and optimized for deployment.

Model inputs and outputs

Inputs

  • Natural language prompts: The model accepts natural language text as input, which can be in the form of questions, instructions, or descriptions.

Outputs

  • Generated natural language text: The model outputs generated text that is semantically relevant to the input prompt. This can include code snippets, explanations, or continuations of the input text.

Capabilities

The deepseek-coder-6.7B-instruct-GGUF model is capable of understanding and generating code in a variety of programming languages, including Python, C/C++, Java, and more. It can be used for tasks such as code completion, code generation, and code explanation. The model has also been fine-tuned to follow instructions and provide helpful, informative responses.

What can I use it for?

The deepseek-coder-6.7B-instruct-GGUF model can be useful for a variety of projects, such as building intelligent code editors, programming assistants, or AI-powered coding tutorials. Developers could integrate the model into their applications to provide real-time code suggestions, automatically generate boilerplate code, or explain programming concepts to users. The model's instruction-following capabilities also make it suitable for use in chatbots or virtual assistants that need to understand and respond to user requests.

Things to try

One interesting thing to try with the deepseek-coder-6.7B-instruct-GGUF model is to provide it with partial code snippets and see how it can complete or expand upon them. You could also try giving the model high-level descriptions of programming tasks and see if it can generate working code to solve those problems. Additionally, you could experiment with the model's ability to understand and respond to natural language instructions, and see how it can be used to build more conversational programming tools.



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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