Instructions to use hf-tiny-model-private/tiny-random-Data2VecAudioForXVector 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-Data2VecAudioForXVector with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForAudioXVector tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecAudioForXVector") model = AutoModelForAudioXVector.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecAudioForXVector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-Data2VecAudioForXVector: direct link, hf CLI and curl.
- Browser
- Download file 344 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-Data2VecAudioForXVector/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-Data2VecAudioForXVector/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-Data2VecAudioForXVector/resolve/main/pytorch_model.bin
344 kB
- Xet hash:
- df2c91db01949bc3cdfbe12a360e0a51e303f7b7787dbb2df47424ee0f8a94f5
- Size of remote file:
- 344 kB
- SHA256:
- 5fcb031496a2e0eed307bb42dc4b3f4ec3f9a92519ae39ff7f18a5b271fdffcd
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