Instructions to use PaddleCI/tiny-random-plato-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- paddlenlp
How to use PaddleCI/tiny-random-plato-mini with paddlenlp:
from paddlenlp.transformers import AutoTokenizer, UnifiedTransformerLMHeadModel tokenizer = AutoTokenizer.from_pretrained("PaddleCI/tiny-random-plato-mini", from_hf_hub=True) model = UnifiedTransformerLMHeadModel.from_pretrained("PaddleCI/tiny-random-plato-mini", from_hf_hub=True) - Notebooks
- Google Colab
- Kaggle
Download model_state.pdparams from PaddleCI/tiny-random-plato-mini: direct link, hf CLI and curl.
- Browser
- Download file 2.07 MB
-
https://huggingface.co/PaddleCI/tiny-random-plato-mini/resolve/main/model_state.pdparams
- Command line
-
hf download hf://PaddleCI/tiny-random-plato-mini/model_state.pdparams
-
curl -L -o model_state.pdparams https://huggingface.co/PaddleCI/tiny-random-plato-mini/resolve/main/model_state.pdparams
2.07 MB
- Xet hash:
- b5504cee6a9f79b65897f864b8fa15fb26fe188c86e2c9394d0ae5868a2f6884
- Size of remote file:
- 2.07 MB
- SHA256:
- d0029526fdd02bbe12ebe8ad5471b883a62151fd9543c59d4620130ce17d9aac
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.