Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use pfe24/whisper-tiny-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pfe24/whisper-tiny-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="pfe24/whisper-tiny-dv")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("pfe24/whisper-tiny-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("pfe24/whisper-tiny-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from pfe24/whisper-tiny-dv: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/pfe24/whisper-tiny-dv/resolve/main/training_args.bin
- Command line
-
hf download hf://pfe24/whisper-tiny-dv/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pfe24/whisper-tiny-dv/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- f54b669a91f7144b2fbfbbf7ea8e703883aaaff4fb318d5efc778757ed87440c
- Size of remote file:
- 5.3 kB
- SHA256:
- d71e900ecb3b52cc0b7c35bdde4c1408f503d3f6f5c5b395daf30b8f2cfe6e2e
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