Instructions to use BricksDisplay/ellie-Bert-VITS2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BricksDisplay/ellie-Bert-VITS2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="BricksDisplay/ellie-Bert-VITS2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BricksDisplay/ellie-Bert-VITS2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from BricksDisplay/ellie-Bert-VITS2: direct link, hf CLI and curl.
- Browser
- Download file 179 Bytes
-
https://huggingface.co/BricksDisplay/ellie-Bert-VITS2/resolve/main/processor_config.json
- Command line
-
hf download hf://BricksDisplay/ellie-Bert-VITS2/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/BricksDisplay/ellie-Bert-VITS2/resolve/main/processor_config.json
179 Bytes
| { | |
| "auto_map": { | |
| "AutoProcessor": "processing_bert_vits2.BertVits2Processor" | |
| }, | |
| "bert_tokenizers": { | |
| "zh": "bert_zh" | |
| }, | |
| "processor_class": "BertVits2Processor" | |
| } | |