Instructions to use Cyleux/oc1b-16bit_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cyleux/oc1b-16bit_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Cyleux/oc1b-16bit_2")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForTextToWaveform extractor = AutoFeatureExtractor.from_pretrained("Cyleux/oc1b-16bit_2") model = AutoModelForTextToWaveform.from_pretrained("Cyleux/oc1b-16bit_2") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoFeatureExtractor, AutoModelForTextToWaveform
extractor = AutoFeatureExtractor.from_pretrained("Cyleux/oc1b-16bit_2")
model = AutoModelForTextToWaveform.from_pretrained("Cyleux/oc1b-16bit_2")Quick Links
Cyleux/oc1b-16bit_2
Full-parameter CSM checkpoint finetuned from unsloth/csm-1b in oc-voice-2026-dualvoice-b200-full-cold-speakerprefix-p90-whine-3ep-20260506.
Source checkpoint path on the Modal checkpoint volume:
/checkpoints/oc-voice-2026-dualvoice-b200-full-cold-speakerprefix-p90-whine-3ep-20260506/checkpoint-19581
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Cyleux/oc1b-16bit_2")