README.md

title: "WhisperFusion" emoji: "🌖" colorFrom: "pink" colorTo: "green" sdk: "docker" python_version: "3.10" sdk_version: "latest" suggested_hardware: "t4-small" suggested_storage: "medium" app_file: "examples/chatbot/html/main.py" app_port: 7860 base_path: "/" fullWidth: false models: ["teknium/OpenHermes-2.5-Mistral-7B"] datasets: [] tags: ["AI", "chatbot", "speech-to-text", "real-time", "TensorRT", "LLM"] pinned: false hf_oauth: false hf_oauth_scopes: [] disable_embedding: false startup_duration_timeout: "30m" custom_headers: cross-origin-embedder-policy: "require-corp" cross-origin-opener-policy: "same-origin" cross-origin-resource-policy: "cross-origin" preload_from_hub:

• "NVIDIA/TensorRT-LLM examples/whisper/whisper_small_en,examples/phi/phi_engine,examples/phi/phi-2" description: "WhisperFusion is an AI chatbot that provides ultra-low latency conversations. It integrates Mistral, a Large Language Model (LLM), on top of the real-time speech-to-text pipeline. It utilizes OpenAI WhisperLive to convert spoken language into text in real-time and is optimized to run as TensorRT engines, ensuring high-performance and low-latency processing." installation: "Install TensorRT-LLM to build Whisper and Mistral TensorRT engines. Refer to the README and the Dockerfile.multi to install the required packages in the base pytorch docker image." usage: "Run the main.py script with the appropriate arguments to start the chatbot." source: "This information is provided by Hugging Face."