Instructions to use almlengineer143/unsth_tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use almlengineer143/unsth_tts with PEFT:
Task type is invalid.
- Transformers
How to use almlengineer143/unsth_tts with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("almlengineer143/unsth_tts", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use almlengineer143/unsth_tts 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 almlengineer143/unsth_tts 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 almlengineer143/unsth_tts to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for almlengineer143/unsth_tts to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="almlengineer143/unsth_tts", max_seq_length=2048, )
- Xet hash:
- 52a42e23e8435b0353e66a598cbf460e43da443362c3a9a8a0f09c5366992cf3
- Size of remote file:
- 55 MB
- SHA256:
- 78ad634e6912af72515f9184312c07ee6bf613a72776f8d4eabe28b9ab2883aa
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