since August 2023, the default fine-tuning features are all based on GPT 3.5+. It’s much simpler, theCasual Fine-Tuningfeatures as well as thedelimitersare not needed anymore. This article will be updated at a later point, and it’s still valid about everything else. ...
since August 2023, the default fine-tuning features are all based on GPT 3.5+. It’s much simpler, theCasual Fine-Tuningfeatures as well as thedelimitersare not needed anymore. This article will be updated at a later point, and it’s still valid about everything else. ...
Explore GPT-3.5 Turbo and discover the transformative potential of fine-tuning. Learn how to customize this advanced language model for niche applications, enhance its performance, and understand the associated costs, safety, and privacy considerations. ...
This is where you need techniques likeretrieval augmentation(RAG) andLLM fine-tuning. However, these techniques often require coding and configurations that are difficult to understand. MonsterGPT, a new tool by MonsterAPI, helps you fine-tune an LLM of your choice by chatting with ChatGPT. Mon...
The fine-tuning script is configured by default to work on less powerful GPUs, but if you have a GPU with more memory, you can increase MICRO_BATCH_SIZE to 32 or 64 in finetune.py . If you have your own instruction tuning dataset, edit DATA_PATH in finetune.py to point to your ow...
Fine-tuning a GPT model on a smaller dataset allows it to perform very well on specialized NLP tasks like text generation, summarization, and question-answering. ChatGPT is a conversational AI system created by OpenAI originally based on the GPT-3 family of large language models, and now GPT...
Fine-tuning stage Reinforcement learning (or PPO optimization) is applied in the fine-tuning stage to fine-tune the model so that ChatGPT provides a more accurate answer to the user(s). As the name suggests, the response (or answer) is generated in the ‘Answer a prompt’ stage where th...
API Requests: Use HTTP requests to send prompts to the ChatGPT API and receive responses. Handling Responses: Process and display the model's responses in your application. Fine-tuning: Customize the model's behavior by providing specific instructions or context. Example API Request POST /v1/eng...
Going back to the prompt used in finetuning, in the previous post we argued that it can be anything, especially for small models, because it’s just a sequence of tokens that anchors the model to the task. The original Alpaca prompt is: ...
Create a Custom Model:Take advantage of OpenAI's fine-tuning capabilities to create a custom ChatGPT. This allows you to tailor the model to your specific use case, making it more attuned to the type of conversation you want to have. ...