Instructions to use Cyleux/oc1b-16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cyleux/oc1b-16bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Cyleux/oc1b-16bit")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForTextToWaveform extractor = AutoFeatureExtractor.from_pretrained("Cyleux/oc1b-16bit") model = AutoModelForTextToWaveform.from_pretrained("Cyleux/oc1b-16bit") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use Cyleux/oc1b-16bit with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Cyleux/oc1b-16bit to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Cyleux/oc1b-16bit to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Cyleux/oc1b-16bit to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Cyleux/oc1b-16bit", max_seq_length=2048, )
File size: 271 Bytes
ad49cba | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"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
}
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