Instructions to use khazarai/Cardiology-TTS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use khazarai/Cardiology-TTS with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/csm-1b") model = PeftModel.from_pretrained(base_model, "khazarai/Cardiology-TTS") - Transformers
How to use khazarai/Cardiology-TTS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="khazarai/Cardiology-TTS")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("khazarai/Cardiology-TTS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from khazarai/Cardiology-TTS: direct link, hf CLI and curl.
- Browser
- Download file 58.1 MB
-
https://huggingface.co/khazarai/Cardiology-TTS/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://khazarai/Cardiology-TTS/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/khazarai/Cardiology-TTS/resolve/main/adapter_model.safetensors
58.1 MB
- Xet hash:
- 0a08e9ec235b781e0159d73417a0ac363fc743093ae614190bdb2281be3a85c4
- Size of remote file:
- 58.1 MB
- SHA256:
- 7f1c272f4aba4fc5c5cc5942b0542ad84659cf15445b555a04e985acb8012681
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