Please use in accordance with Llama-2's license terms.
The prompt for our WizardCoder is:
Below is an instruction that describes a task. Write a response that appropriately completes the request.
WizardCoder is a Code Large Language Model (LLM) that has been fine-tuned using the Evol-Instruct method. The model has been trained on a large dataset of code instruction-following tasks and has demonstrated exceptional performance on code-related tasks.
WizardCoder is a Code LLM that has been fine-tuned using the Evol-Instruct method. The model has been trained on a large dataset of code instruction-following tasks and has demonstrated superior performance compared to other open-source and closed LLMs on prominent code generation benchmarks.
WizardCoder can be used for a variety of code-related tasks, including code generation, code completion, and code summarization. Here are some examples of input prompts that can be used with the model:
- Code generation: Given a description of a programming task, generate the corresponding code. Example input: "Write a Python function that takes a list of integers as input and returns the sum of all even numbers in the list."
- Code completion: Given an incomplete code snippet, complete the code. Example input: "def multiply(a, b): \n return a * b _"
- Code summarization: Given a long code snippet, generate a summary of the code. Example input: “Write a Python program that reads a CSV file and calculates the average of a specific column.”
WizardCoder was trained on a large dataset of code instruction-following tasks. The dataset was evolved through the Evol-Instruct method and contains a variety of programming tasks with different levels of complexity. The dataset is not publicly available.
WizardCoder-Python-34B has demonstrated exceptional performance on code-related tasks. The model has outperformed other open-source and closed LLMs on prominent code generation benchmarks, including HumanEval (73.2%), HumanEval+, and MBPP(61.2%).
WizardCoder-Python-34B-V1.0 attains the second position in HumanEval Benchmarks, surpassing GPT4 (2023/03/15, 73.2 vs. 67.0), ChatGPT-3.5 (73.2 vs. 72.5) and Claude2 (73.2 vs. 71.2).
WizardCoder could generate unethical, harmful, or misleading information. Therefore, it is important to use the model responsibly and to address the ethical and societal implications of its use. Additionally, the dataset used to train the model is not publicly available, which limits the ability of researchers to replicate the results and evaluate the model on new tasks.
We disclaim all liability with respect to the actions or omissions of the Vendor, and we encourage you to exercise caution and to ensure that you are comfortable with these practices before utilizing the AI models hosted on our site.
- Model Type IDText To Text
- DescriptionWizardCoder is a Code Large Language Model (LLM) that has been fine-tuned on Llama2 excelling in python code generation tasks and has demonstrated superior performance compared to other open-source and closed LLMs on prominent code generation benchmarks.
- Last UpdatedNov 29, 2023
- Use Case