Instructions to use codewithdark/csm-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codewithdark/csm-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="codewithdark/csm-1b")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForTextToWaveform extractor = AutoFeatureExtractor.from_pretrained("codewithdark/csm-1b") model = AutoModelForTextToWaveform.from_pretrained("codewithdark/csm-1b") - Notebooks
- Google Colab
- Kaggle
| { | |
| "chunk_length_s": null, | |
| "feature_extractor_type": "EncodecFeatureExtractor", | |
| "feature_size": 1, | |
| "overlap": null, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "CsmProcessor", | |
| "return_attention_mask": true, | |
| "sampling_rate": 24000 | |
| } | |