CodeLlama-7b-hf-neuron-24xlarge

Neuronx model for codellama/CodeLlama-7b-hf

This repository contains AWS Inferentia2 and neuronx compatible checkpoints for codellama/CodeLlama-7b-hf. You can find detailed information about the base model on its Model Card.

This model has been exported to the neuron format using specific input_shapes and compiler parameters detailed in the paragraphs below.

It has been compiled to run on an inf2.24xlarge instance on AWS.

Please refer to the 🤗 optimum-neuron documentation for an explanation of these parameters.

Usage on Amazon SageMaker

coming soon

Usage with 🤗 optimum-neuron

>>> from optimum.neuron import pipeline

>>> p = pipeline('text-generation', 'aws-neuron/CodeLlama-7b-hf-neuron-24xlarge')
>>> p("import socket\n\ndef ping_exponential_backoff(host: str):",
    do_sample=True,
    top_k=10,
    temperature=0.1,
    top_p=0.95,
    num_return_sequences=1,
    max_length=200,
)
[{'generated_text': 'import socket\n\ndef ping_exponential_backoff(host: str):\n    """\n    Ping a host with exponential backoff.\n\n    :param host: Host to ping\n    :return: True if host is reachable, False otherwise\n    """\n    for i in range(1, 10):\n        try:\n            socket.create_connection((host, 80), 1).close()\n            return True\n        except OSError:\n            time.sleep(2 ** i)\n    return False\n\n\ndef ping_exponential_backoff_with_timeout(host: str, timeout: int):\n    """\n    Ping a host with exponential backoff and timeout.\n\n    :param host: Host to ping\n    :param timeout: Timeout in seconds\n    :return: True if host is reachable, False otherwise\n    """\n    for'}]

This repository contains tags specific to versions of neuronx. When using with 🤗 optimum-neuron, use the repo revision specific to the version of neuronx you are using, to load the right serialized checkpoints.

Arguments passed during export

input_shapes

{
  "batch_size": 1,
  "sequence_length": 2048,
}

compiler_args

{
  "auto_cast_type": "fp16",
  "num_cores": 12,
}