Instructions to use Langboat/mengzi-t5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Langboat/mengzi-t5-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Langboat/mengzi-t5-base") model = AutoModelForSeq2SeqLM.from_pretrained("Langboat/mengzi-t5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Langboat/mengzi-t5-base: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/Langboat/mengzi-t5-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Langboat/mengzi-t5-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Langboat/mengzi-t5-base/resolve/main/pytorch_model.bin
990 MB
- Xet hash:
- 2feb4b58367d1dfb21d9fcad42cca1f25139800dbec2710d4627975ad6d904ad
- Size of remote file:
- 990 MB
- SHA256:
- de2ffe9a9ddcf05b154b56c77fc44765a195375192cf7f64a95c440a91830576
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