OpenVINO™ Test Drive#

Find a model on Hugging Face and import it.

Chat with LLMs via the Playground tab. You can export an LLM by clicking the Export model button.

Use the Performance metrics tab to get model performance metrics on your computer or an edge device.

Upload files and create knowledge base for RAG (Retrieval-Augmented Generation), using Knowledge base tab.

The knowledge base can be used for text generation with LLM models.

You can also upload a document directly, using the Playground` tab.

Import a VLM for image analysis.

Select the VLM from the My models section, upload an image and analyze it.

Import a Whisper model for video transcription.

Select the speech-to-text LLM from the My models section, and upload a video for transcription.

You can search for words in the transcript or download it.

Use the Performance metrics tab to get performance metrics of the LLM on your computer or an edge device.

Import an image generation LLM from a predefined set of popular models or from Hugging Face, using Import model -> Hugging Face.

Select the LLM from the My models section and start the chat to generate an image. You can export the model by clicking the Export model button.

You can download the generated image.

Use the Performance metrics tab to get performance metrics of the LLM on your computer or an edge device.

Download the deployment code for a model in the OpenVINO IR format trained by Intel® Geti™ (refer to the Intel® Geti™ documentation for more details).

Import the deployment code into OpenVINO™ Test Drive, using the Import model and then Local disk buttons.

Use the Live inference tab to run and visualize results of inference of individual images.

For batch inference, use the Batch inference tab and provide paths to the folder with input images, as well as one for batch inference results. You can do so by filling out the Source folder and Destination folder fields. Click Start to start batch inference.