Fine-tune GPT-2 with your custom text dataset
One-Stop Gemma Model Fine-tuning, Quantization & Conversion
Create powerful AI models without code
Perform basic tasks like code generation, file conversion, and system diagnostics
YoloV1 by luismidv
Create powerful AI models without code
Lora finetuning guide
Fine-tune LLMs to generate clear, concise, and natural language responses
Load and activate a pre-trained model
Float16 to covert
Set up and launch an application from a GitHub repo
Transformers Fine Tuner: A user-friendly Gradio interface
Fine-tune Gemma models on custom datasets
Project is a Fine Tuning Tool designed to help users customize and fine-tune the GPT-2 model using their own text datasets. It provides an efficient and user-friendly way to adapt the model to specific tasks or domains, enabling tailored outputs for various applications.
Who is Project best suited for?
Project is ideal for developers, researchers, and data scientists looking to adapt GPT-2 for specific tasks or domains.
What format should my dataset be in?
Your dataset should be in a plain text format, with each entry separated by a newline or other delimiter as specified in the tool's documentation.
Can I fine-tune the model for multiple tasks at once?
Yes, Project supports multi-task fine-tuning, allowing you to train the model for various applications simultaneously.