saschaschramm/chatgpt

This is stars and forks stats for /saschaschramm/chatgpt repository. As of 25 Apr, 2024 this repository has 136 stars and 10 forks.

ChatGPT ChatGPT is a text-based AI assistant by OpenAI. This is an analysis of ChatGPT. Analysis Models available via chat.openai.com GPT-3.5 title slug max_tokens description Default (GPT-3.5) text-davinci-002-render-sha 8191 Our fastest model, great for most everyday tasks. Default (GPT-3.5) (Mobile) text-davinci-002-render-sha-mobile 8191 Our fastest model, great for most everyday tasks. Code Interpreter text-davinci-002-render-sha-code-interpreter nan nan Plugins text-davinci-002-render-sha-plugin nan nan GPT-4 title slug max_tokens description GPT-4 gpt-4 4095 Our most capable model, great for tasks that require creativity and advanced reasoning. Plugins gpt-4-plugins 8192 An experimental model that knows when and how to use plugins GPT-4 (Mobile, V2) gpt-4-mobile 4095 Our most capable model, great for tasks that require creativity and advanced reasoning. Code Interpreter gpt-4-code-interpreter nan nan Models available via platform.openai.com Model Max tokens Training data (pre-training) gpt-4-0613 8192 Up to Sep 2021 gpt-4-32k-0613 32768 Up to Sep 2021 gpt-3.5-turbo-0613 4096 Up to Sep 2021 gpt-3.5-turbo-16k-0613 16384 Up to Sep 2021 gpt-4-0314 8192 Up to Sep 2021 gpt-4-32k-0314 32768 Up to Sep 2021 gpt-3.5-turbo-0301 4096 Up to Sep 2021 Completion If we send the message [{"role": "user", "content": "13+37="}] to the model, it returns the following chat completion response: Model Completion gpt-3.5-turbo-0613 Link gpt-4-0613 Link Vocabulary The ChatGPT models employ a distinct vocabulary compared to their predecessors. The models use a cl100k_base vocabulary with 100,000 tokens, where each token encodes an average of 3.7 characters in English. For a detailed analysis, see vocab.ipynb. Additionally, these models employ the Chat Markup Language. Tokenizer The number of prompt tokens and completion tokens are computed as follows (see OpenAI-Cookbook for details): prompt_tokens = ['<|im_start|>', 'user', '\n', '13', '+', '37', '=', '<|im_end|>', '<|im_start|>', 'assistant', '<|message|>'] # len(tokens) is 11 completion_tokens = ['50'] # len(tokens) is 1 Performance We have evaluated the ChatGPT model gpt-4-0613 with the HumanEval dataset. Out of 164 programming problems, the model can solve 86.59%. Model name Pass@1 Date Comment Results Prompt  gpt-4-0613 86.59% 2023-06-13 https://platform.openai.com/ Link Complete the following code. Use ```python to put the completed Python code in markdown quotes:\n{code}  gpt-3.5-turbo-0613 71.34% 2023-06-13 https://platform.openai.com/ Link Complete the following code. Use ```python to put the completed Python code in markdown quotes:\n{code}  gpt-4-0314 78.66% 2023-03-17 https://platform.openai.com/ Link Complete the following code:\n{code}  gpt-3.5-turbo-0301 74.39% 2023-04-24 https://platform.openai.com/ Link Complete the following code. Use ```python to put the Python code in markdown quotes:\n{code}  text-davinci-002-render-sha 70.12% 2023-02-19 https://chat.openai.com/  text-davinci-002-render 56.10% 2022-12-03 https://chat.openai.com/ cushman-ml 56.10% 2022-10-23 Copilot code-davinci-002 46.95% 2022-10-23 https://platform.openai.com/ code-cushman-001 32.93% 2022-10-23 https://platform.openai.com/