Llama Code 7B

📖 Introduction

Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 34 billion parameters. This is the repository for the base 7B version in the Hugging Face Transformers format. This model is designed for general code synthesis and understanding.

Task Type	Description
Completion	A task to generate natural continuation texts based on input prompt.

🔄 Compatibility Matrix

To ensure smooth integration, please refer to the compatibility matrix below. It outlines the compatible versions of the model, instill-core, and the python-sdk.

Instill Core Version	Python SDK Version
>= v0.51.0	>= v0.18.0

Note: Always ensure that you are using compatible versions to avoid unexpected issues.

🚀 Preparation

Follow this guide to get your custom model up and running! But before you do that, please read through the following sections to have all the necessary files ready.

Install Python SDK

Install the compatible python-sdk version according to the compatibility matrix:

pip install instill-sdk=={version}

Get model weights

To download the fine-tuned model weights, please execute the following command:

git clone https://huggingface.co/codellama/CodeLlama-7b-hf

Test model image

After you've built the model image, and before pushing the model onto any Instill Core instance, you can test if the model can be successfully run locally first, by running the following command:

instill run instill-ai/llamacode-7b -g -i '{"prompt": "go func("}'

The input payload should strictly follow the the below format

{
  "prompt": "..."
}

A successful response will return a similar output to that shown below.

2024-09-11 02:03:26,813.813 INFO     [Instill] Starting model image...
2024-09-11 02:03:37,228.228 INFO     [Instill] Deploying model...
2024-09-11 02:04:37,750.750 INFO     [Instill] Running inference...
2024-09-11 02:04:42,434.434 INFO     [Instill] Outputs:
[{'data': {'choices': [{'content': 'go func(interface{}) error, interceptor '
                                   'grpc.UnaryServerInterceptor) (interface{}, '
                                   'error) {\n'
                                   '\tin := new(SayHelloReq)\n'
                                   '\tif err := dec(in); err!= nil {',
                        'created': 1725991482,
                        'finish-reason': 'length',
                        'index': 0}]}}]
2024-09-11 02:04:46,147.147 INFO     [Instill] Done

Here is the list of flags supported by instill run command

• -t, --tag: tag for the model image, default to latest
• -g, --gpu: to pass through GPU from host into container or not, depends on if gpu is enabled in the config.
• -i, --input: input in json format

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Happy Modeling! 💡