Instructions to use FirstPotatoCoder/Furina_5e_fft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FirstPotatoCoder/Furina_5e_fft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="FirstPotatoCoder/Furina_5e_fft")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("FirstPotatoCoder/Furina_5e_fft") model = AutoModelForTextToWaveform.from_pretrained("FirstPotatoCoder/Furina_5e_fft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForTextToWaveform
processor = AutoProcessor.from_pretrained("FirstPotatoCoder/Furina_5e_fft")
model = AutoModelForTextToWaveform.from_pretrained("FirstPotatoCoder/Furina_5e_fft", device_map="auto")Quick Links
Uploaded model
- Developed by: FirstPotatoCoder
- License: apache-2.0
- Finetuned from model : unsloth/csm-1b
This csm model was trained 2x faster with Unsloth and Huggingface's TRL library.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="FirstPotatoCoder/Furina_5e_fft")