Instructions to use hf-internal-testing/tiny-random-EncodecModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-EncodecModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-EncodecModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-EncodecModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-EncodecModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-EncodecModel: direct link, hf CLI and curl.
- Browser
- Download file 93.2 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-EncodecModel/resolve/ccc7ec0382d71464988d186ae801a7b144e72007/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-EncodecModel@ccc7ec0382d71464988d186ae801a7b144e72007/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-EncodecModel/resolve/ccc7ec0382d71464988d186ae801a7b144e72007/pytorch_model.bin
93.2 MB
- Xet hash:
- 7d81b4c170244bb897def74a732329e72dd48d30d2559a00f48f58261fedd834
- Size of remote file:
- 93.2 MB
- SHA256:
- a71caa24bce598c90dcbdbb0458dce52f7479996c69c78a4257d5262088ad3bc
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