Instructions to use sensenova/piccolo-large-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sensenova/piccolo-large-zh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sensenova/piccolo-large-zh")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sensenova/piccolo-large-zh") model = AutoModel.from_pretrained("sensenova/piccolo-large-zh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sensenova/piccolo-large-zh: direct link, hf CLI and curl.
- Browser
- Download file 651 MB
-
https://huggingface.co/sensenova/piccolo-large-zh/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://sensenova/piccolo-large-zh@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sensenova/piccolo-large-zh/resolve/refs%2Fpr%2F2/pytorch_model.bin
651 MB
- Xet hash:
- c59d6acf55b8325413c61089edd176afb7478fee8a20cdbbc2078da9dcf462ca
- Size of remote file:
- 651 MB
- SHA256:
- f087280a2c06ae0cdc156fb24c1f177faf8faa2532b2566c8ff4b70ce15481db
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