Instructions to use Martingkc/Llama3.1_1B_dMel_TTS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Martingkc/Llama3.1_1B_dMel_TTS with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Martingkc/Llama3.1_1B_dMel_TTS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from Martingkc/Llama3.1_1B_dMel_TTS: direct link, hf CLI and curl.
- Browser
- Download file 3.2 GB
-
https://huggingface.co/Martingkc/Llama3.1_1B_dMel_TTS/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://Martingkc/Llama3.1_1B_dMel_TTS/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/Martingkc/Llama3.1_1B_dMel_TTS/resolve/main/adapter_model.safetensors
3.2 GB
- Xet hash:
- 6a3b6602f94d9c1519075d4bcd046802b0c4fd9e022818d07fec882f81a3e852
- Size of remote file:
- 3.2 GB
- SHA256:
- 8767fa7d6b7cd53a176cd6ccc198510a841e4ddad9972c3b133d1cc9dba09e2a
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