Automatic Speech Recognition
Transformers
Safetensors
sensevoice_small
sensevoice
speech-recognition
Instructions to use MigoXV/SenseVoiceSmall with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MigoXV/SenseVoiceSmall with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="MigoXV/SenseVoiceSmall")# pip install -U transformers accelerate # Load model directly from transformers import SenseVoiceSmall model = SenseVoiceSmall.from_pretrained("MigoXV/SenseVoiceSmall", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download conversion_manifest.json from MigoXV/SenseVoiceSmall: direct link, hf CLI and curl.
- Browser
- Download file 2.61 kB
-
https://huggingface.co/MigoXV/SenseVoiceSmall/resolve/main/conversion_manifest.json
- Command line
-
hf download hf://MigoXV/SenseVoiceSmall/conversion_manifest.json
-
curl -L -o conversion_manifest.json https://huggingface.co/MigoXV/SenseVoiceSmall/resolve/main/conversion_manifest.json
2.61 kB
| { | |
| "source_repo": "FunAudioLLM/SenseVoiceSmall", | |
| "source_sha256": { | |
| "config.yaml": "f71e239ba36705564b5bf2d2ffd07eece07b8e3f2bbf6d2c99d8df856339ac19", | |
| "model.pt": "833ca2dcfdf8ec91bd4f31cfac36d6124e0c459074d5e909aec9cabe6204a3ea", | |
| "am.mvn": "29b3c740a2c0cfc6b308126d31d7f265fa2be74f3bb095cd2f143ea970896ae5", | |
| "chn_jpn_yue_eng_ko_spectok.bpe.model": "aa87f86064c3730d799ddf7af3c04659151102cba548bce325cf06ba4da4e6a8" | |
| }, | |
| "tensor_count": 917, | |
| "tensor_alignment": "bitwise_equal", | |
| "dtype": "float32", | |
| "vocab_size": 25055, | |
| "input_size": 560, | |
| "files_sha256": { | |
| "config.json": "5f8900034949397cd2b30f1681bab99fa9e53a7e4ad62e0b0517c38795d940ad", | |
| "model.safetensors": "4544976a2bd0f5f96b190dff3c3988ddeae7a3ed97563a8b5d8303bd16aa6834", | |
| "cmvn.npy": "0ea4208f06f3d2de26a7e7d741cf864c3db53a7fb687a32d27b210f81172c8ec", | |
| "preprocessor_config.json": "eb877ba05961d74b67bbb5a38d6d42623afb4043f772a27c7678e062d52cbe1d", | |
| "tokenizer_config.json": "1c2b2cd7ff10b0307d36fc3901af6043922682397cb4e5063a78c17cbfcf2d28", | |
| "special_tokens_map.json": "96bdbb8504d9967606e5f661ccc7cbbac44a3661af863a7a58614670a0ccab33", | |
| "tokenizer.model": "aa87f86064c3730d799ddf7af3c04659151102cba548bce325cf06ba4da4e6a8", | |
| "processor_config.json": "736a07203533fd3eba60413f85620805134cbb5df4ddccc81c6c201f2ab09b06", | |
| "MODEL_LICENSE.txt": "7dba975a2069691db4992b0592d70828b330d2f8a30a71450f4e152a554e84f8", | |
| "UPSTREAM-CODE-MIT.txt": "f382b62dcc61fc566b9215b1e3b604b539bfd96ed52ae1eeff5090f6dc176057", | |
| "README.md": "41707d08443b74b05b03490db082ba8e03ca2e85d163a119fd8f910bc57c5fe0", | |
| "alignment_summary.json": "f196ab829df26e3927f8811ffb64a7aad7e7313c06d34ca9cbb51fc5c117fa39", | |
| "sensevoice_hf/__init__.py": "3eed1c8f8406fe21f624ab103f0f88936aecf9f68f64731f5d9e8da3210177c3", | |
| "sensevoice_hf/configuration_sensevoice.py": "e8c61fbb57912583af9cbf5c0ae2a98afe7288cf19a1b451ccd0bc4b380af2d7", | |
| "sensevoice_hf/ctc_alignment.py": "99179071096f458540b6d3fb3d4b2f5cb187e99925e3d9df3bde9d0e59524640", | |
| "sensevoice_hf/feature_extraction_sensevoice.py": "15eb452d18a089b6313515eeed64967fdae0823e90f334b53e8c0b9ba38213f2", | |
| "sensevoice_hf/modeling_sensevoice.py": "c9544e2ee4373f080e4c9d58b324cc52fd438100b08bfbe2e0c4b3fe589ff7a8", | |
| "sensevoice_hf/postprocess.py": "dd4eb0b380e2bd6c64d30b45d32a3a873057773469d65888b1f9a2e6bba3576b", | |
| "sensevoice_hf/processing_sensevoice.py": "edb09b8c9cbba7d06d515cb86b8b1ec9876a4a3ec49824f7317db38be696f2d3", | |
| "sensevoice_hf/tokenization_sensevoice.py": "4e9f18aa6fbbc23b765f88c94ee10519a30844cd0aa105dd10fb52677272dee6" | |
| } | |
| } | |