Instructions to use xezpeleta/pitz-v0-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xezpeleta/pitz-v0-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="xezpeleta/pitz-v0-ft")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("xezpeleta/pitz-v0-ft") model = AutoModelForCausalLM.from_pretrained("xezpeleta/pitz-v0-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 83af2366f7b46a21c77a12bfb4917258d6bc859b9def22c347f9dd8d71f7c815
- Size of remote file:
- 22.8 MB
- SHA256:
- 044e2a10201774018db120391980464472baabf223bd353cea49b17da0b66abc
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