Codellama
Models by this creator
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CodeLlama-70b-hf
304
The CodeLlama-70b-hf is a large language model developed by codellama that is part of the Code Llama family of models. It is a 70 billion parameter model designed for general code synthesis and understanding. The model comes in various sizes ranging from 7 billion to 70 billion parameters, with different variants tailored for Python, Instruct, and the base general model. The maintainer's profile provides more information about the creator of this model. Model inputs and outputs The CodeLlama-70b-hf model takes text as input and generates text as output. It is an auto-regressive language model that uses an optimized transformer architecture. Inputs Text input to the model Outputs Generated text output from the model Capabilities The CodeLlama-70b-hf model has capabilities for code completion, infilling, instructions/chat, and is a Python specialist. It can be used for a variety of code synthesis and understanding tasks. What can I use it for? The CodeLlama-70b-hf model can be used for commercial and research purposes related to code generation and understanding. The model's capabilities make it useful for projects like code assistants, code generation tools, and other applications that require synthesizing or comprehending code. Developers can fine-tune the model further for their specific use cases. Things to try Developers can experiment with using the CodeLlama-70b-hf model for tasks like generating code snippets, auto-completing code, and following programming instructions. The model's size and versatility make it a powerful tool for exploring the boundaries of what large language models can do for code-related applications.
Updated 5/28/2024
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CodeLlama-7b-hf
299
The CodeLlama-7b-hf is a 7 billion parameter generative text model developed by codellama and released through the Hugging Face Transformers library. It is part of the broader Code Llama collection of language models ranging in size from 7 billion to 70 billion parameters. The base CodeLlama-7b-hf model is designed for general code synthesis and understanding tasks. It is available alongside specialized variants like the CodeLlama-7b-Python-hf for Python-focused applications, and the CodeLlama-7b-Instruct-hf for safer, more controlled use cases. Model inputs and outputs The CodeLlama-7b-hf is an auto-regressive language model that takes in text as input and generates new text as output. It can be used for a variety of natural language processing tasks beyond just code generation, including: Inputs Text:** The model accepts arbitrary text as input, which it then uses to generate additional text. Outputs Text:** The model outputs new text, which can be used for tasks like code completion, text infilling, and language modeling. Capabilities The CodeLlama-7b-hf model is capable of a range of text generation and understanding tasks. It excels at code completion, where it can generate relevant code snippets to extend a given codebase. The model can also be used for code infilling, generating text to fill in gaps within existing code. Additionally, it has strong language understanding capabilities, allowing it to follow instructions and engage in open-ended dialogue. What can I use it for? The CodeLlama-7b-hf model is well-suited for a variety of software development and programming-related applications. Developers can use it to build intelligent code assistants that provide real-time code completion and generation. Data scientists and machine learning engineers could leverage the model's capabilities to automate the generation of boilerplate code or experiment with novel model architectures. Researchers in natural language processing may find the model useful for benchmarking and advancing the state-of-the-art in areas like program synthesis and code understanding. Things to try One interesting aspect of the CodeLlama-7b-hf model is its ability to handle long-range dependencies in code. Try providing it with a partially completed function or class definition and observe how it can generate coherent and relevant code to fill in the missing parts. You can also experiment with prompting the model to explain or refactor existing code snippets, as its language understanding capabilities may allow it to provide insightful commentary and suggestions.
Updated 5/28/2024
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CodeLlama-34b-Instruct-hf
267
The CodeLlama-34b-Instruct-hf is a large language model developed by codellama as part of the Code Llama collection. This 34 billion parameter model is designed specifically for general code synthesis and understanding tasks. It builds upon the base Code Llama model and adds specialized instruction-following capabilities for safer and more controlled deployment as a code assistant application. Other variants in the Code Llama family include the Python-focused 34B model and the 7B and 13B instruct-tuned versions. Model inputs and outputs The CodeLlama-34b-Instruct-hf model takes in text input and generates text output. It is particularly adept at code-related tasks like completion, infilling, and following instructions. The model can handle a wide range of programming languages, but is specialized for Python. Inputs Text prompts for the model to continue or complete Outputs Generated text, often in the form of code snippets or responses to instructions Capabilities The CodeLlama-34b-Instruct-hf model is capable of a variety of code-related tasks. It can complete partially written code, fill in missing code segments, and follow instructions to generate new code. The model also has strong language understanding abilities, allowing it to engage in code-related dialog and assist with programming tasks. What can I use it for? The CodeLlama-34b-Instruct-hf model can be used for a wide range of applications related to code generation and understanding. Potential use cases include code completion tools, programming assistants, and even automated programming. Developers could integrate the model into their workflows to boost productivity and creativity. However, as with all large language models, care must be taken when deploying the CodeLlama-34b-Instruct-hf to ensure safety and ethical use. Developers should review the Responsible Use Guide before integrating the model. Things to try One interesting aspect of the CodeLlama-34b-Instruct-hf model is its ability to handle code-related instructions and dialog. Developers could experiment with prompting the model to explain programming concepts, debug code snippets, or even pair program by taking turns generating code. The model's strong language understanding capabilities make it well-suited for these types of interactive coding tasks.
Updated 5/28/2024
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CodeLlama-70b-Instruct-hf
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The CodeLlama-70b-Instruct-hf model is part of the Code Llama family of large language models developed by Meta. It is a 70 billion parameter model that has been fine-tuned for instruction following and safer deployment compared to the base Code Llama model. Similar models in the Code Llama family include the 7B, 34B, and 13B Instruct variants, as well as the 70B base model and 70B Python specialist. Model inputs and outputs The CodeLlama-70b-Instruct-hf model is a text-to-text transformer that takes in text and generates text output. It has been designed to excel at a variety of code-related tasks including code completion, infilling, and following instructions. Inputs Text prompts Outputs Generated text Capabilities The CodeLlama-70b-Instruct-hf model is capable of performing a wide range of code-related tasks. It can generate and complete code snippets, fill in missing parts of code, and follow instructions for coding tasks. The model is also a specialist in the Python programming language. What can I use it for? The CodeLlama-70b-Instruct-hf model is well-suited for building code assistant applications, automating code generation and completion, and enhancing programmer productivity. Developers could use it to build tools that help with common coding tasks, provide explanations and examples, or generate new code based on natural language prompts. The model's large size and instruction-following capabilities make it a powerful resource for commercial and research use cases involving code synthesis and understanding. Things to try One interesting experiment would be to see how the CodeLlama-70b-Instruct-hf model performs on open-ended coding challenges or competitions. Its ability to understand and follow detailed instructions, combined with its strong Python skills, could give it an edge in generating novel solutions to complex programming problems. Researchers and developers could also explore fine-tuning or prompting techniques to further enhance the model's capabilities in specific domains or applications.
Updated 5/27/2024
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CodeLlama-7b-Instruct-hf
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CodeLlama-7b-Instruct-hf is a 7 billion parameter large language model developed by codellama that has been fine-tuned for code generation and conversational tasks. It is part of the Code Llama family of models, which range in size from 7 billion to 34 billion parameters. The Meta-Llama-3-8B-Instruct and Meta-Llama-3-70B-Instruct are similar large language models developed by Meta that have also been optimized for dialogue and safety. Model inputs and outputs CodeLlama-7b-Instruct-hf is an autoregressive language model that takes in text as input and generates text as output. It can handle a wide range of natural language tasks such as code generation, text completion, and open-ended conversation. Inputs Natural language text Outputs Generated natural language text Generated code Capabilities CodeLlama-7b-Instruct-hf can assist with a variety of tasks including code completion, code infilling, following instructions, and general language understanding. It has been shown to perform well on benchmarks for programming and dialogue applications. What can I use it for? The CodeLlama-7b-Instruct-hf model can be used for a wide range of applications that require natural language processing and generation, such as code assistants, chatbots, and text generation tools. Developers can fine-tune the model further on domain-specific data to customize it for their needs. Things to try Some interesting things to try with CodeLlama-7b-Instruct-hf include prompting it to engage in open-ended dialogue, asking it to explain complex programming concepts, or using it to generate novel code snippets. Developers should keep in mind the model's capabilities and limitations when designing their applications.
Updated 5/28/2024
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CodeLlama-34b-hf
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CodeLlama-34b-hf is a large language model developed by codellama that is designed for general code synthesis and understanding tasks. It is part of the CodeLlama collection, which ranges in size from 7 billion to 70 billion parameters. The 34 billion parameter version is the base model in the Hugging Face Transformers format. Other similar models in the CodeLlama family include the CodeLlama-70b-hf, which is a larger 70 billion parameter version, as well as variants fine-tuned for Python and instruction following. Model inputs and outputs CodeLlama-34b-hf is an autoregressive language model that takes in text as input and generates text as output. It can be used for a variety of code-related tasks such as code completion, infilling, and instruction following. Inputs Text prompts for code generation or understanding Outputs Synthesized code or text responses Capabilities CodeLlama-34b-hf is capable of generating high-quality code in response to prompts. It can also be used for tasks like code understanding, code translation, and providing explanations about code. The model has been trained on a large corpus of code and text data, giving it broad knowledge and capabilities. What can I use it for? CodeLlama-34b-hf can be used for a variety of applications that involve code generation, understanding, or interaction. Some potential use cases include: Building code editing or generation tools to assist developers Automating code-related workflows like bug fixing or refactoring Generating sample code or documentation for educational purposes Integrating code capabilities into chatbots or virtual assistants Things to try One interesting aspect of CodeLlama-34b-hf is its ability to handle open-ended prompts and generate relevant, coherent code. You could try providing the model with a high-level description of a task or program you want to build, and see what kind of code it generates to address that need. The model's broad knowledge allows it to draw on a wide range of programming concepts and techniques to come up with creative solutions.
Updated 5/28/2024
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CodeLlama-13b-Instruct-hf
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CodeLlama-13b-Instruct-hf is a 13 billion parameter version of the Code Llama family of large language models developed by Meta. The Code Llama models are designed for general code synthesis and understanding, with variants focused on Python and instruction-following. This 13B instruct-tuned model is optimized for safe deployment as a code assistant. The CodeLlama-7b-Instruct-hf and CodeLlama-70b-hf are similar models in the Code Llama family, with 7 billion and 70 billion parameters respectively. Like this 13B model, they offer capabilities in code completion, infilling, instructions/chat, and Python-specific tasks. Model inputs and outputs Inputs Text input only Outputs Generates text only, including code Capabilities CodeLlama-13b-Instruct-hf can assist with a variety of code-related tasks, such as code completion, infilling, and following natural language instructions. It is particularly adept at understanding and generating Python code. The model has been carefully trained to provide safe and helpful responses. What can I use it for? The CodeLlama-13b-Instruct-hf model can be used for a range of commercial and research applications involving code generation and understanding. This includes building code assistants, code completion tools, and programming tutors. The model's strong performance on Python-specific tasks makes it well-suited for Python-focused applications. When deploying the model, it's important to test for safety and align it with your specific use case, as with any large language model. The Responsible Use Guide provides guidance on best practices. Things to try Try using CodeLlama-13b-Instruct-hf to generate code completions, refine existing code snippets, or provide natural language instructions for coding tasks. Experiment with different prompting techniques and generation parameters to see how the model responds. Remember to thoroughly test for safety and alignment with your use case.
Updated 5/28/2024
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CodeLlama-7b-Python-hf
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CodeLlama-7b-Python-hf is a 7 billion parameter language model developed by codellama as part of the Code Llama family of models. It is designed as a Python specialist, with capabilities in areas like code completion, infilling, and instruction following. The model is available in a range of sizes from 7 billion to 70 billion parameters, with variants focused on Python and safer deployment through instruct-tuning. Similar models include the CodeLlama-70b-hf, a larger 70 billion parameter base model, the CodeLlama-34b-hf with 34 billion parameters, and the CodeLlama-7b-Instruct-hf and CodeLlama-13b-Instruct-hf variants focused on instruction following. Model inputs and outputs CodeLlama-7b-Python-hf is an autoregressive language model that takes in text as input and generates new text as output. The model is specialized for Python code and can be used for a variety of code-related tasks. Inputs Text prompts in English Outputs Generated text, which can include Python code, natural language, or a combination of the two Capabilities CodeLlama-7b-Python-hf can be used for tasks like code completion, where the model continues a partially written piece of code, or code infilling, where the model fills in missing sections of code. The model can also be used for general language understanding and generation, making it suitable for tasks like instruction following and chatbot applications. What can I use it for? The CodeLlama-7b-Python-hf model can be used for a variety of Python-related applications, such as building code assistants, generating example code, or enhancing existing IDEs and coding tools. The model's capabilities in areas like code completion and understanding could make it useful for automating repetitive coding tasks or assisting developers in their work. Things to try One interesting aspect of CodeLlama-7b-Python-hf is its ability to combine natural language and code in its outputs. You could try giving the model prompts that mix descriptions of desired functionality with partial code, and see how it completes the code to match the natural language instructions. Another interesting experiment would be to provide the model with open-ended coding challenges or algorithm problems and observe how it approaches solving them.
Updated 5/28/2024
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CodeLlama-70b-Python-hf
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The CodeLlama-70b-Python-hf model is part of the Code Llama collection of generative text models ranging in scale from 7 billion to 70 billion parameters. This 70 billion parameter model is specialized for the Python programming language and designed for general code synthesis and understanding tasks. It can be used alongside other Code Llama models like the base 70B version or the 7B Python-specialized model. Model inputs and outputs The CodeLlama-70b-Python-hf model takes in text as input and generates text as output. It is optimized for code-related tasks like code completion, infilling, and instruction following, with a particular focus on the Python programming language. Inputs Text prompts Outputs Generated text, such as Python code completions or responses to instructions Capabilities The CodeLlama-70b-Python-hf model can be used for a variety of code-related tasks, including code completion, code synthesis, and following instructions to generate code. For example, it could be used to auto-complete a partially written Python function, or to generate a Python script based on a high-level description of its functionality. What can I use it for? The CodeLlama-70b-Python-hf model could be useful for developers looking to accelerate their coding workflows, data scientists automating routine data analysis tasks, or even hobbyists creating fun programming projects. The model's Python specialization makes it well-suited for applications that involve generating or understanding Python code, such as code assistants, automated programming tools, or educational applications. Things to try One interesting thing to try with the CodeLlama-70b-Python-hf model is giving it partially completed code snippets and seeing how it fills in the gaps. This could help identify areas where the model excels at understanding and generating Python syntax and logic. You could also try providing the model with high-level instructions or prompts and see the types of Python programs it generates in response.
Updated 5/27/2024
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CodeLlama-34b-Python-hf
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CodeLlama-34b-Python-hf is a 34 billion parameter language model from the Code Llama family, fine-tuned specifically for Python code synthesis and understanding. It is part of a larger collection of Code Llama models ranging from 7 billion to 70 billion parameters, with variants designed for general code tasks, Python, and instruction following. The similar models include smaller 7B and 13B Python versions, as well as larger 70B models. Model inputs and outputs CodeLlama-34b-Python-hf is an autoregressive language model that takes in text input and generates text output. It is designed to excel at code-related tasks such as code completion, infilling, and instruction following. Inputs Text prompts Outputs Generated text, including code snippets and responses to instructions Capabilities The CodeLlama-34b-Python-hf model is highly capable at a variety of code-related tasks. It can generate original code, complete partially written code, and even follow natural language instructions to write code. The model's Python specialization allows it to handle the Python programming language particularly well. What can I use it for? CodeLlama-34b-Python-hf and the broader Code Llama family of models are intended for commercial and research use in programming-related applications. The Python-specialized variant could be used to build interactive code assistants, augment developer productivity through code completion, or generate synthetic training data for machine learning. The Responsible Use Guide provides important guidance on the safe and ethical deployment of these models. Things to try One interesting aspect of CodeLlama-34b-Python-hf is its ability to seamlessly mix natural language and code. You could prompt the model with a partially written Python function and ask it to continue the implementation, or provide a high-level description of a task and have the model generate the corresponding code. The model's strong performance on Python-specific constructs makes it a powerful tool for automating code-related workflows.
Updated 5/28/2024