Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use xbilek25/whisper-medium-en-cv-8.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xbilek25/whisper-medium-en-cv-8.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="xbilek25/whisper-medium-en-cv-8.0")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("xbilek25/whisper-medium-en-cv-8.0") model = AutoModelForSpeechSeq2Seq.from_pretrained("xbilek25/whisper-medium-en-cv-8.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from xbilek25/whisper-medium-en-cv-8.0: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/xbilek25/whisper-medium-en-cv-8.0/resolve/13d039dac87618ab7c13beb46b442b03f14bc6c5/training_args.bin
- Command line
-
hf download hf://xbilek25/whisper-medium-en-cv-8.0@13d039dac87618ab7c13beb46b442b03f14bc6c5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/xbilek25/whisper-medium-en-cv-8.0/resolve/13d039dac87618ab7c13beb46b442b03f14bc6c5/training_args.bin
5.5 kB
- Xet hash:
- 2e05d9c24a2aced50241923d745de807ce219db9547f35ce2fefd65845be27fd
- Size of remote file:
- 5.5 kB
- SHA256:
- 526bef21064f2e68c134341fe79e0bbfefd79cf145230e382821f62518fbc77d
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