Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use xbilek25/wme_30s_speed_20_1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xbilek25/wme_30s_speed_20_1.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="xbilek25/wme_30s_speed_20_1.0")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("xbilek25/wme_30s_speed_20_1.0") model = AutoModelForSpeechSeq2Seq.from_pretrained("xbilek25/wme_30s_speed_20_1.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from xbilek25/wme_30s_speed_20_1.0: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/xbilek25/wme_30s_speed_20_1.0/resolve/main/training_args.bin
- Command line
-
hf download hf://xbilek25/wme_30s_speed_20_1.0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/xbilek25/wme_30s_speed_20_1.0/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 019995e73a1bad443d9aed6ec2483ab5d39dc8cf375a19f45b3efd8875913591
- Size of remote file:
- 5.43 kB
- SHA256:
- 800ac1c66ea7f2ca3ae2788d15b6ebde7f6e271c98a35dcc01c703a950dc36c7
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