Instructions to use FirstPotatoCoder/Furina_10e_lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FirstPotatoCoder/Furina_10e_lm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="FirstPotatoCoder/Furina_10e_lm")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForTextToWaveform extractor = AutoFeatureExtractor.from_pretrained("FirstPotatoCoder/Furina_10e_lm") model = AutoModelForTextToWaveform.from_pretrained("FirstPotatoCoder/Furina_10e_lm") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use FirstPotatoCoder/Furina_10e_lm with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for FirstPotatoCoder/Furina_10e_lm to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for FirstPotatoCoder/Furina_10e_lm to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for FirstPotatoCoder/Furina_10e_lm to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="FirstPotatoCoder/Furina_10e_lm", max_seq_length=2048, )
- Xet hash:
- 81d258377e0848cd8ffb4f1aa03788ad0cfc7b9b634a07184892e45d1892b183
- Size of remote file:
- 4.15 GB
- SHA256:
- abb8104749fcf6643e39c59a128e74f7c765ba05fd41741968f8a784b9a133b0
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