Transformers Fine Tuner: A user-friendly Gradio interface
YoloV1 by luismidv
Perform basic tasks like code generation, file conversion, and system diagnostics
Login to use AutoTrain for custom model training
Upload ML models to Hugging Face Hub from your browser
Fine Tuning sarvam model
Create stunning graphic novels effortlessly with AI
Create powerful AI models without code
Create powerful AI models without code
Load and activate a pre-trained model
Lora finetuning guide
First attempt
Fine-tune Gemma models on custom datasets
Transformers Fine Tuner is a user-friendly Gradio interface designed for fine-tuning transformer models on custom datasets. It allows users to adapt pre-trained models like BERT, RoBERTa, and others to specific tasks such as text classification, sentiment analysis, or question answering. This tool simplifies the fine-tuning process, making it accessible to both researchers and practitioners.
• Support for Multiple Models: Compatible with popular transformer architectures like BERT, RoBERTa, and DistilBERT.
• Custom Dataset Upload: Easily upload and use your own dataset for fine-tuning in formats like CSV or JSON.
• Hyperparameter Tuning: Adjust training parameters such as learning rate, batch size, and number of epochs.
• Real-Time Metrics: Monitor training progress with metrics like accuracy, loss, and F1-score displayed in real-time.
• Pre-Trained Model Selection: Choose from a variety of pre-trained models to suit your specific task.
• Export Options: Download the fine-tuned model for deployment in other applications.
What formats does the tool support for dataset upload?
The Transformers Fine Tuner supports datasets in CSV or JSON formats. Ensure your data is properly formatted for the specific task (e.g., text classification).
Can I use the tool for tasks other than NLP?
While the tool is primarily designed for NLP tasks, you can experiment with other tasks involving text data. For non-NLP tasks, consider alternative tools.
Is the tool completely free to use?
The Transformers Fine Tuner offers a free version with limitations on model size and dataset capacity. For larger-scale applications, consider upgrading to a paid plan.