ifmain_-_StableGPT4-Micro-1.6B-awq

Quantization made by Richard Erkhov.

Github

Discord

Request more models

StableGPT4-Micro-1.6B - AWQ

• Model creator: https://huggingface.co/ifmain/
• Original model: https://huggingface.co/ifmain/StableGPT4-Micro-1.6B/

Original model description:

base_model: stabilityai/stablelm-2-zephyr-1_6b library_name: transformers pipeline_tag: text-generation datasets:

• openchat/openchat_sharegpt4_dataset
• ifmain/gpt4myself

---

StableGPT4-Micro-1.6B

StableGPT4-Micro-1.6B is a conversational AI model trained on the ChatGPT chats, designed to generate text-based responses for various conversational scenarios. This model has been fine-tuned and optimized for stability and reliability, providing coherent and contextually appropriate responses across a wide range of topics.

Usage

You can interact with the StableGPT4-Micro-1.6B model by providing it with prompts in JSON format. Each prompt should include the role of the speaker ("user" or "assistant") and the text of their message.

Example

{"role": "user", "text": "Hi"}
{"role": "assistant", "text": "Hello! How can I help you today? If you have any questions or need assistance, feel free to ask."}
{"role": "user", "text": "write hello world in c++"}
{"role": "assistant", "text": "Here's a simple `HelloWorld` program in C++:\n```cpp\n#include <iostream>\n\nint main() {\n    std::cout << \"Hello, World!\" << std::endl;\n    return 0;\n}\n```\nThis code uses the `<iostream>` standard library to create a `std::cout` stream and print the string \"Hello, World!\" to the standard output. The `return 0` statement indicates that the program has finished running and returns the control to the user. You can run this program on your C++ compiler's command line or integrated development environment (IDE) to see the output."}

Test

You can use gen.py to test the model.

Notes

• The model is trained to provide helpful and informative responses based on the input prompts.
• While the model strives to maintain coherence and relevance, it may occasionally generate unexpected or nonsensical outputs.

Please feel free to experiment with the model and provide feedback on its performance and usability.