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
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Download README.md from FirstPotatoCoder/Furina_5e_fft: direct link, hf CLI and curl.
- Browser
- Download file 553 Bytes
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https://huggingface.co/FirstPotatoCoder/Furina_5e_fft/resolve/main/README.md
- Command line
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hf download hf://FirstPotatoCoder/Furina_5e_fft/README.md
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curl -L -o README.md https://huggingface.co/FirstPotatoCoder/Furina_5e_fft/resolve/main/README.md
553 Bytes
metadata
base_model: unsloth/csm-1b
tags:
- text-generation-inference
- transformers
- unsloth
- csm
- trl
license: apache-2.0
language:
- en
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.
