Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Korean
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use gingercake01/STT_1000audio_basev3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gingercake01/STT_1000audio_basev3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="gingercake01/STT_1000audio_basev3")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("gingercake01/STT_1000audio_basev3") model = AutoModelForSpeechSeq2Seq.from_pretrained("gingercake01/STT_1000audio_basev3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gingercake01/STT_1000audio_basev3: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/gingercake01/STT_1000audio_basev3/resolve/main/training_args.bin
- Command line
-
hf download hf://gingercake01/STT_1000audio_basev3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gingercake01/STT_1000audio_basev3/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 8d593143d8e338d488d116f5ad10f6add33cf85ad4f7031039f99d5c1b7e46f8
- Size of remote file:
- 5.3 kB
- SHA256:
- 4e08edf7de79f9fba9a3ff06a82d834b10b2833e7d58d2bd2f20ebd5ffbb6212
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