Instructions to use Nathan9/xcodec_mini_infer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nathan9/xcodec_mini_infer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Nathan9/xcodec_mini_infer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download modules/__init__.py from Nathan9/xcodec_mini_infer: direct link, hf CLI and curl.
- Browser
- Download file 525 Bytes
-
https://huggingface.co/Nathan9/xcodec_mini_infer/resolve/main/modules/__init__.py
- Command line
-
hf download hf://Nathan9/xcodec_mini_infer/modules/__init__.py
-
curl -L -o __init__.py https://huggingface.co/Nathan9/xcodec_mini_infer/resolve/main/modules/__init__.py
525 Bytes
| # Copyright (c) Meta Platforms, Inc. and affiliates. | |
| # All rights reserved. | |
| # | |
| # This source code is licensed under the license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| """Torch modules.""" | |
| # flake8: noqa | |
| from .conv import ( | |
| pad1d, | |
| unpad1d, | |
| NormConv1d, | |
| NormConvTranspose1d, | |
| NormConv2d, | |
| NormConvTranspose2d, | |
| SConv1d, | |
| SConvTranspose1d, | |
| ) | |
| from .lstm import SLSTM | |
| from .seanet import SEANetEncoder, SEANetDecoder | |
| from .transformer import StreamingTransformerEncoder | |