Code generation is the process of automatically generating code from a given input. This can be done for a variety of purposes, such as creating documentation, generating test cases, or even writing entire programs. In recent years, there has been a growing interest in using large language models (LLMs) for code generation. LLMs are neural networks that have been trained on vast amounts of text data, and they have shown impressive results on a variety of natural language processing tasks.
In this article, we will show how to use Amazon SageMaker to generate code using Code Llama 70B and Mixtral 8x7B, two of the most powerful LLMs available today.
Code Llama 70B
Code Llama 70B is a 70-billion parameter LLM that was developed by Google. It has been trained on a massive dataset of code and natural language text, and it has shown state-of-the-art performance on a variety of code generation tasks.
Mixtral 8x7B
Mixtral 8x7B is a 8×7-billion parameter LLM that was developed by DeepMind. It is based on the same Transformer architecture as Code Llama 70B, but it has been trained on a different dataset. Mixtral 8x7B has also shown impressive results on a variety of code generation tasks, and it is particularly well-suited for generating code in multiple programming languages.
Using Code Llama 70B and Mixtral 8x7B on Amazon SageMaker
Amazon SageMaker is a cloud-based machine learning platform that makes it easy to train and deploy machine learning models. SageMaker provides a variety of tools for working with LLMs, including a managed notebook service and a set of pre-built Docker images.
To use Code Llama 70B and Mixtral 8x7B on Amazon SageMaker, you can follow these steps:
- Create a SageMaker notebook instance.
- Open a terminal window in the notebook instance.
- Install the SageMaker Python SDK.
- Load the Code Llama 70B or Mixtral 8x7B model into memory.
- Generate code using the model.
The following code snippet shows how to generate code using Code Llama 70B:
“`python
import sagemaker
from sagemaker.huggingface import HuggingFace
# Create a HuggingFace model
model = HuggingFace(
model_id=google/code-llama-70b,
transformers_version=4.25.1,
pytorch_version=1.12.1,
py_version=py39,
)
# Generate code
generated_code = model.predict(
inputs=
Generate a function that takes a list of numbers and returns the average.
)
print(generated_code)
“`
The following code snippet shows how to generate code using Mixtral 8x7B:
“`python
import sagemaker
from sagemaker.huggingface import HuggingFace
# Create a HuggingFace model
model = HuggingFace(
model_id=deepmind/mixer-8x7b,
transformers_version=4.25.1,
pytorch_version=1.12.1,
py_version=py39,
)
# Generate code
generated_code = model.predict(
inputs=
Generate a function that takes a list of numbers and returns the average.
)
print(generated_code)
“`
Conclusion
Code Llama 70B and Mixtral 8x7B are two of the most powerful LLMs available today. They can be used to generate code for a variety of purposes, and they are easy to use on Amazon SageMaker.
Kind regards
J.O. Schneppat
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