Instructions to use jrnw/sesame_csm_finetune_16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jrnw/sesame_csm_finetune_16bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="jrnw/sesame_csm_finetune_16bit")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("jrnw/sesame_csm_finetune_16bit") model = AutoModelForTextToWaveform.from_pretrained("jrnw/sesame_csm_finetune_16bit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Uploaded finetuned model
- Developed by: jrnw
- License: apache-2.0
- Finetuned from model : unsloth/csm-1b
This csm model was trained 2x faster with Unsloth and Huggingface's TRL library.
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