Instructions to use audo/orpheus-3b-0.1-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use audo/orpheus-3b-0.1-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="audo/orpheus-3b-0.1-ft")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("audo/orpheus-3b-0.1-ft") model = AutoModelForCausalLM.from_pretrained("audo/orpheus-3b-0.1-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.bin from audo/orpheus-3b-0.1-ft: direct link, hf CLI and curl.
- Browser
- Download file 26.4 GB
-
https://huggingface.co/audo/orpheus-3b-0.1-ft/resolve/main/optimizer.bin
- Command line
-
hf download hf://audo/orpheus-3b-0.1-ft/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/audo/orpheus-3b-0.1-ft/resolve/main/optimizer.bin
26.4 GB
- Xet hash:
- 8f7ea1be6b01a452cbca46e7cc8ed0e898511296d84d3cb890043b9a1eab0e9e
- Size of remote file:
- 26.4 GB
- SHA256:
- d5bee80349108dea555669a02d057c6bb9412b85d2c3e6a5c069b6d7a271244d
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