Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Korean
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use lcjln/AIME_Project_The_Final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lcjln/AIME_Project_The_Final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lcjln/AIME_Project_The_Final")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("lcjln/AIME_Project_The_Final") model = AutoModelForSpeechSeq2Seq.from_pretrained("lcjln/AIME_Project_The_Final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lcjln/AIME_Project_The_Final: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/lcjln/AIME_Project_The_Final/resolve/main/training_args.bin
- Command line
-
hf download hf://lcjln/AIME_Project_The_Final/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lcjln/AIME_Project_The_Final/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 81a7133cc4181f1a3fdbb2b04574d543923940fae3b3f81f342241bd9cff6d29
- Size of remote file:
- 5.37 kB
- SHA256:
- 02fea28e1c4241960c774b3be2afcc18bd4861e226aa2608b8c95089f2a24576
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