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
OffVox — copia de respaldo de modelos
Copia sin modificar de los modelos que descarga la app OffVox (diario y reuniones por voz, 100% local). Existe por si las ubicaciones originales cambian o desaparecen. No es un repositorio oficial de OpenAI, NVIDIA, Google ni Alibaba, y ninguno de ellos lo respalda.
Los modelos de voz están extraídos tal cual de los paquetes .tar.bz2 de
sherpa-onnx, para instalarse sin descomprimir. Cada carpeta lleva su
licencia.
| Carpeta | Modelo y origen | Licencia |
|---|---|---|
whisper/{tiny,base,small}/ |
OpenAI Whisper, export int8 de sherpa-onnx (sherpa-onnx-whisper-*.tar.bz2) |
MIT, © 2022 OpenAI |
parakeet-tdt-0.6b-v3/ |
nvidia/parakeet-tdt-0.6b-v3, export int8 de sherpa-onnx (sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8.tar.bz2) |
CC BY 4.0, © NVIDIA |
titanet-small/ |
NVIDIA NeMo TitaNet-small, export ONNX de sherpa-onnx | Apache-2.0, © NVIDIA |
gemma-4-e2b-it/ |
litert-community/gemma-4-E2B-it-litert-lm @ 6e5c4f1e, basado en google/gemma-4-E2B-it |
Apache-2.0 (Gemma 4 license), Gemma 4 © Google DeepMind |
qwen2.5-1.5b-instruct/ |
litert-community/Qwen2.5-1.5B-Instruct @ 19edb84c, basado en Qwen/Qwen2.5-1.5B-Instruct |
Apache-2.0, © 2024 Alibaba Cloud |
SHA-256
Idénticos a los originales (comprobado al subirlos).
181938105e0eefd105961417e8da75903eacda102c4fce9ce90f50b97139a63c gemma-4-e2b-it/gemma-4-E2B-it.litertlm
179e50c43d1a9de79c8a24149a2f9bac6eb5981823f2a2ed88d655b24248db4e parakeet-tdt-0.6b-v3/decoder.int8.onnx
acfc2b4456377e15d04f0243af540b7fe7c992f8d898d751cf134c3a55fd2247 parakeet-tdt-0.6b-v3/encoder.int8.onnx
3164c13fc2821009440d20fcb5fdc78bff28b4db2f8d0f0b329101719c0948b3 parakeet-tdt-0.6b-v3/joiner.int8.onnx
d58544679ea4bc6ac563d1f545eb7d474bd6cfa467f0a6e2c1dc1c7d37e3c35d parakeet-tdt-0.6b-v3/tokens.txt
faa60663b333290c1496c499828b21d3e3254a788cacd8cce917ce0f761a2dc9 qwen2.5-1.5b-instruct/Qwen2.5-1.5B-Instruct_multi-prefill-seq_q8_ekv4096.litertlm
ad4a1802485d8b34c722d2a9d04249662f2ece5d28a7a039063ca22f515a789e titanet-small/nemo_en_titanet_small.onnx
9759d217388a01b3a4c7c15533201067b48ae819c4daafc8624e64b9409dc02d whisper/base/decoder.int8.onnx
0b8fb1304b6109976038efff5ace81720e00386f3ff6b54ee8c75291ca0a1e11 whisper/base/encoder.int8.onnx
b34b360dbb493e781e479794586d661700670d65564001f23024971d1f2fa126 whisper/base/tokens.txt
acad50b5c782696e91b55914cc5ab4f756f1532f76e22aa6fc615f39fb69a8ee whisper/small/decoder.int8.onnx
4cbe7b22fa9026b843b60a68640c747de05bafb1a11b57edc0e66c232d9f33a9 whisper/small/encoder.int8.onnx
b34b360dbb493e781e479794586d661700670d65564001f23024971d1f2fa126 whisper/small/tokens.txt
d2fece8dd42771f1df975c6c0445770d0c292bf7547c2cae04a6c0cc57540925 whisper/tiny/decoder.int8.onnx
d24fb083ae3b1041fc24e97971d60e280c9342201fbb67b0ab428a8b4a51a434 whisper/tiny/encoder.int8.onnx
b34b360dbb493e781e479794586d661700670d65564001f23024971d1f2fa126 whisper/tiny/tokens.txt
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