Codellama 70B Instruct - Details

Codellama 70B Instruct is a large language model developed by Code Llama, a company, featuring 70b parameters. It is designed for instruct tasks with a primary focus on Python coding. The model operates under the Llama 2 Community License Agreement (LLAMA-2-CLA) and the Llama Code Acceptable Use Policy (Llama-CODE-AUP).

Codellama 70B Instruct is a large language model with 70b parameters, part of a suite of models designed for code synthesis and understanding. It includes specialized variants like Code Llama - Python for Python tasks and Code Llama - Instruct for instruction-following and safer use. The models are trained on code and text data, with the 70B version supporting up to 16k tokens of context. This collection spans parameter sizes from 7B to 70B, offering flexibility for diverse coding applications.

Codellama 70B Instruct is a 70b parameter model, placing it in the very large models category, which excels at complex coding tasks but demands significant computational resources. Its 16k context length falls under long contexts, enabling it to handle extended code sequences and maintain coherence over longer texts, though this requires more memory and processing power. The combination of 70b parameters and 16k context makes it highly effective for intricate programming challenges, such as analyzing large codebases or generating detailed documentation, while also reflecting the trade-offs of resource intensity.

• Parameter Size: 70b
• Context Length: 16k

Codellama 70B Instruct is a large language model designed for code synthesis, code understanding, and code generation, with commercial and research use as its primary focus. Its 70b parameter size and 16k context length make it a possible tool for tasks like automating code writing, analyzing complex codebases, or assisting developers in creating software. Possible applications could include generating code snippets, translating between programming languages, or supporting collaborative coding workflows. However, these possible uses require careful evaluation to ensure they align with specific needs and constraints. The model’s capabilities might also be explored for code assistant applications, where it could provide real-time suggestions or debug code. Still, possible benefits and limitations must be thoroughly investigated before deployment.

• commercial and research use
• code synthesis
• code understanding
• code assistant applications
• code generation

Codellama 70B Instruct is a large language model with 70b parameters and a 16k context length, making it a possible tool for tasks like code synthesis, code understanding, and code generation. Possible applications could include automating code writing, analyzing complex codebases, or supporting developers in creating software. Possible uses might also extend to translating between programming languages or assisting with collaborative coding workflows. Possible benefits could arise in research settings or commercial projects where code efficiency and accuracy are critical. However, these possible applications require thorough evaluation to ensure they meet specific requirements and constraints.

• code synthesis
• code understanding
• code assistant applications
• code generation

Codellama 70B Instruct with the q4 quantization offers a possible balance between precision and performance, requiring a GPU with at least 24GB VRAM for models up to 32B parameters, but for the 70B version, multiple GPUs with 48GB+ VRAM total are likely necessary. System memory should be at least 32GB, and adequate cooling and power supply are essential. These possible requirements depend on the specific implementation and workload.

• fp16, q2, q3, q4, q5, q6, q8

Codellama 70B Instruct is a large language model with 70b parameters and a 16k context length, optimized for code synthesis, code understanding, and code generation. It is part of a suite including variants like Code Llama - Python and Code Llama - Instruct, designed for commercial and research use with a focus on coding tasks.

Huggingface Model Page
Ollama Model Page