Model Overview

Description:

Code Llama is a large language AI model built from a collection of models capable of generating code in response to prompts. It is based on Llama 2.

Terms of use:

By accessing this model, you are agreeing to the LLama 2 Terms and Conditions of the License, Acceptable Use Policy and Meta’s Privacy Policy

References(s):

Code Llama: Open Foundation Models for Code paper

Meta's Code Llama model card

Model Architecture:

Architecture Type: Transformer

Network Architecture: Llama 2

Input:

Input Format: Text

Input Parameters: Temperature, Top P (Nucleus Sampling)

Output:

Output Format: Text (code)

Output Parameters: Max Output Tokens

Software Integration:

Supported Hardware Platform(s): RTX 4090, Ada GPUs

Supported Operating System(s): Windows

Training & Finetuning:

Dataset:

Near-duplicated dataset of publicly available code, propriety of Meta. 8% of samples data are sourced from natural language datasets related to code and containing discussions about code and code snippets included in natural language questions or answers. To help the model retain natural language understanding skills, dataset also inclues a small proportion of batches from a natural language dataset.

Inference:

Engine: TRT-LLM

Test Hardware: RTX 4090

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It can generate code, and natural language about code, from both code and natural language prompts.","Model Overview\n--------------\n\n### Description:\n\nCode Llama is a large language AI model built from a collection of models capable of generating code in response to prompts. It is based on [Llama 2](https://ai.meta.com/llama/).\n\n### Terms of use:\n\nBy accessing this model, you are agreeing to the LLama 2 Terms and Conditions of the [License](https://ai.meta.com/resources/models-and-libraries/llama-downloads), [Acceptable Use Policy](https://l.facebook.com/l.php?u=https%3A%2F%2Fai.meta.com%2Fllama%2Fuse-policy&h=AT17YXIWa1dxwuzDq96w614_oshaUCWIQYHHHf9BgC0X5UK39DW2tpSP6NzkeadQVs0XBaNlFSo4nydTUcKB5r-Kn4OLs_5IbMEZYAf5hUvyzIwx8-mLom2ic1vw5rSPFUoc9A) and [Meta’s Privacy Policy](https://www.facebook.com/privacy/policy/)\n\n### References(s):\n\n[Code Llama: Open Foundation Models for Code](https://ai.meta.com/research/publications/code-llama-open-foundation-models-for-code/) paper \n\n[Meta's Code Llama](https://github.com/facebookresearch/codellama/blob/main/MODEL_CARD.md) model card\n\n### Model Architecture:\n\n**Architecture Type:** Transformer \n\n**Network Architecture:** Llama 2\n\n### Input:\n**Input Format:** Text \n\n**Input Parameters:** Temperature, Top P (Nucleus Sampling)\n\n### Output:\n\n**Output Format:** Text (code) \n\n**Output Parameters:** Max Output Tokens\n\n### Software Integration:\n\n**Supported Hardware Platform(s):** RTX 4090, Ada GPUs \n\n**Supported Operating System(s):** Windows\n\nTraining & Finetuning:\n----------------------\n\n### Dataset:\n\nNear-duplicated dataset of publicly available code, propriety of Meta. 8% of samples data are sourced from natural language datasets related to code and containing discussions about code and code snippets included in natural language questions or answers. 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