Instructions to use re-skill/orpheus-tj-early with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use re-skill/orpheus-tj-early with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="re-skill/orpheus-tj-early")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("re-skill/orpheus-tj-early") model = AutoModelForCausalLM.from_pretrained("re-skill/orpheus-tj-early", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bcc6ec675df3e3e1caa5c6db9aefef6dc659f151e23fe4be1eff553ae4ec1234
- Size of remote file:
- 5.71 kB
- SHA256:
- 6ae3a63a586d3931d9e23626048b802fcf8bc1726c8f737ab5d3eab08151237e
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