Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use xbilek25/whisper-medium-en-cv-6.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xbilek25/whisper-medium-en-cv-6.0 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-6.0")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("xbilek25/whisper-medium-en-cv-6.0") model = AutoModelForSpeechSeq2Seq.from_pretrained("xbilek25/whisper-medium-en-cv-6.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from xbilek25/whisper-medium-en-cv-6.0: direct link, hf CLI and curl.
- Browser
- Download file 3.06 GB
-
https://huggingface.co/xbilek25/whisper-medium-en-cv-6.0/resolve/main/model.safetensors
- Command line
-
hf download hf://xbilek25/whisper-medium-en-cv-6.0/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/xbilek25/whisper-medium-en-cv-6.0/resolve/main/model.safetensors
3.06 GB
- Xet hash:
- 246d05cf6a87359a0eb8ecb206ba60b1b0b9fdeea4752c19045f7211ca9fbf37
- Size of remote file:
- 3.06 GB
- SHA256:
- 78af28e37a6541f1a6172b2ce0d671e4ccf051f1bffee904621dee2d0c1a9038
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