Instructions to use maydixit/llama_v5_toolace with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maydixit/llama_v5_toolace with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("maydixit/llama_v5_toolace", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d65f16d9842b33d9e3b6d29a9a3e37cf95bb587e5f29745f6b4aa8bb306b309
- Size of remote file:
- 545 MB
- SHA256:
- 56846f100c9d89a1e3af5747b7b5f1dd30493baa2fd19da277babcc9d8f9cb4c
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