Instructions to use Dpn82/offvox-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use Dpn82/offvox-models with LiteRT-LM:
# LiteRT-LM runs on various platforms (Android, iOS, Windows, Linux, macOS, IoT, Web/WASM) # and supports many APIs (C++, Python, Kotlin, Swift, JavaScript, Flutter). # For platform-specific integration guides, please refer to the official developer website: # https://ai.google.dev/edge/litert-lm # To try LiteRT-LM, the easiest way is to use our CLI tool. # 1. Install the LiteRT-LM CLI tool: pip install -U litert-lm # 2. Download and run this model locally: # See: https://ai.google.dev/edge/litert-lm/cli # A single .litertlm file in the repo is picked automatically; otherwise the CLI asks which one to run # (or pass its name right after the repo id). litert-lm run \ --from-huggingface-repo=Dpn82/offvox-models \ --prompt="Write me a poem"
- Notebooks
- Google Colab
- Kaggle
Download whisper/tiny/decoder.int8.onnx from Dpn82/offvox-models: direct link, hf CLI and curl.
- Browser
- Download file 89.9 MB
-
https://huggingface.co/Dpn82/offvox-models/resolve/main/whisper/tiny/decoder.int8.onnx
- Command line
-
hf download hf://Dpn82/offvox-models/whisper/tiny/decoder.int8.onnx
-
curl -L -o decoder.int8.onnx https://huggingface.co/Dpn82/offvox-models/resolve/main/whisper/tiny/decoder.int8.onnx
89.9 MB
- Xet hash:
- f45f4a788d292ee1cb92a09ce6ad1496acc7648c20bfe32ca1f5e088aeedb87f
- Size of remote file:
- 89.9 MB
- SHA256:
- d2fece8dd42771f1df975c6c0445770d0c292bf7547c2cae04a6c0cc57540925
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