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 model.safetensors from hf-internal-testing/tiny-random-EncodecModel: direct link, hf CLI and curl.
- Browser
- Download file 93.1 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-EncodecModel/resolve/refs%2Fpr%2F6/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-EncodecModel@refs/pr/6/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-EncodecModel/resolve/refs%2Fpr%2F6/model.safetensors
93.1 MB
- Xet hash:
- 254856c8f8697d04fe1252a69cbf39d04dc2e54fdb8f4fb59720b4e7459c0c83
- Size of remote file:
- 93.1 MB
- SHA256:
- 2f6f5e77680f49f4fc9e0e665ccd65e9112ac4e18e2ce681c66f6373e350fbb4
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