Instructions to use Novix/SongGenerationtwo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SongGeneration
How to use Novix/SongGenerationtwo with SongGeneration:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 1,076 Bytes
6972b23 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@File : pretrained.py
@Time : 2023/8/8 下午7:22
@Author : waytan
@Contact : waytan@tencent.com
@License : (C)Copyright 2023, Tencent
@Desc : Loading pretrained models.
"""
from pathlib import Path
import yaml
from .apply import BagOfModels
from .htdemucs import HTDemucs
from .states import load_state_dict
def add_model_flags(parser):
group = parser.add_mutually_exclusive_group(required=False)
group.add_argument("-s", "--sig", help="Locally trained XP signature.")
group.add_argument("-n", "--name", default=None,
help="Pretrained model name or signature. Default is htdemucs.")
parser.add_argument("--repo", type=Path,
help="Folder containing all pre-trained models for use with -n.")
def get_model_from_yaml(yaml_file, model_file):
bag = yaml.safe_load(open(yaml_file))
model = load_state_dict(HTDemucs, model_file)
weights = bag.get('weights')
segment = bag.get('segment')
return BagOfModels([model], weights, segment)
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