Instructions to use yzhuang/MetaTree with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yzhuang/MetaTree with Transformers:
# Load model directly from transformers import AutoTokenizer, LlamaForMetaTree tokenizer = AutoTokenizer.from_pretrained("yzhuang/MetaTree") model = LlamaForMetaTree.from_pretrained("yzhuang/MetaTree", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d24e8d126d0617f20016e0aada7bca22394ed83aa5fcb759ca369fe95bb84f81
- Size of remote file:
- 303 MB
- SHA256:
- 55bf1637016acbbb5d93f35d81ed2ca804272c0ed8dcf9c4908b16da57374a69
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.