Instructions to use Cyleux/oc1b-16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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,
)

oc1b-16bit / tokenizer_config.json

Commit History

(Trained with Unsloth)

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Cyleux commited on Jul 25, 2025

Commit History

(Trained with Unsloth) ad49cba verified

(Trained with Unsloth)

ad49cba
verified