Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use TheRains/yt-special-batch4-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheRains/yt-special-batch4-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TheRains/yt-special-batch4-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("TheRains/yt-special-batch4-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("TheRains/yt-special-batch4-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from TheRains/yt-special-batch4-tiny: direct link, hf CLI and curl.
- Browser
- Download file 151 MB
-
https://huggingface.co/TheRains/yt-special-batch4-tiny/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://TheRains/yt-special-batch4-tiny/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/TheRains/yt-special-batch4-tiny/resolve/main/pytorch_model.bin
151 MB
- Xet hash:
- 4d1cc85212b4462a1279d3e60adb4af2b998a574930d7722dde32ad934bd4884
- Size of remote file:
- 151 MB
- SHA256:
- 2217cb96ddcee391ef2fd21f95dfe75e2f1cb65d02cd778823016bfd0de4f951
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.