Instructions to use thomasgauthier/csm-1b-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thomasgauthier/csm-1b-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="thomasgauthier/csm-1b-hf")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("thomasgauthier/csm-1b-hf") model = AutoModel.from_pretrained("thomasgauthier/csm-1b-hf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training Question
#1
by electronicalias - opened
Hi there,
Really great work on this, thank you.
QQ. regarding the training, I assume you can just focus on training speaker_1 in order to force the model to respond in a particular voice. I have some voice audio which I'm testing with this and other models, so the .jsonl could be formatted:
{
"messages": [
{
"role": "speaker_1",
"content": [
{"type": "text", "text": "A voice I want to force the model to use to speak."},
{"type": "audio", "url": "clips/example_audio_01.wav"}
]
},
{
"role": "speaker_1",
"content": [
{"type": "text", "text": "Another example of the voice I want the model to use."},
{"type": "audio", "url": "clips/example_audio_02.wav"}
]
}
],
"training_mask": [false, true]
}
I'm doing this as I've not had much success with voice cloning.
Thanks.