Instructions to use hf-tiny-model-private/tiny-random-Data2VecAudioForCTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-Data2VecAudioForCTC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-tiny-model-private/tiny-random-Data2VecAudioForCTC")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCTC tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecAudioForCTC") model = AutoModelForCTC.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecAudioForCTC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-Data2VecAudioForCTC: direct link, hf CLI and curl.
- Browser
- Download file 296 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-Data2VecAudioForCTC/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-Data2VecAudioForCTC/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-Data2VecAudioForCTC/resolve/main/pytorch_model.bin
296 kB
- Xet hash:
- 51ac7b03dd22c356afa90b3ddce7ba951c5a50ef45b754bb749722f21921ebea
- Size of remote file:
- 296 kB
- SHA256:
- 7637e1554d64e49b5eb9958ed26531663495595554b4d23a51627618c73a2c2c
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