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| title: Station Vision TTS | |
| emoji: ๐ | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 4.44.1 | |
| app_file: app.py | |
| pinned: false | |
| # Station Vision TTS Space | |
| Remote Gradio demo for the Japanese station-announcement pipeline: | |
| 1. `LiquidAI/LFM2.5-VL-450M-Extract` extracts compact JSON from an image. | |
| 2. `LiquidAI/LFM2-350M` turns the JSON into one short Japanese announcement. | |
| 3. `3bitquantizers/lfm25-audio-jp-station-yamanote-merged-v1-all-langs-static` synthesizes live audio. | |
| ## Deploy | |
| Create a GPU-backed Gradio Space under `3bitquantizers`, then copy these files to the Space root: | |
| ```bash | |
| cp app.py requirements.txt README.md /path/to/space/ | |
| cp ../image_to_station_audio.py /path/to/space/ | |
| ``` | |
| Set Space secrets: | |
| - `HF_TOKEN`: read access to private `3bitquantizers` model repos. | |
| Optional Space variables: | |
| - `VL_MODEL_ID` | |
| - `PROMPT_MODEL_ID` | |
| - `TTS_MODEL_ID` | |
| - `MAX_TTS_TOKENS` | |
| Use a 24 GB GPU tier or larger for the first smoke. The app keeps models warm and queues requests one at a time. | |