Transformers
PyTorch
Safetensors
Chinese
t5
text2text-generation
prompt
Text2Text-Generation
text-generation-inference
Instructions to use mxmax/Chinese_Chat_T5_Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mxmax/Chinese_Chat_T5_Base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mxmax/Chinese_Chat_T5_Base") model = AutoModelForSeq2SeqLM.from_pretrained("mxmax/Chinese_Chat_T5_Base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from mxmax/Chinese_Chat_T5_Base: direct link, hf CLI and curl.
- Browser
- Download file 742 kB
-
https://huggingface.co/mxmax/Chinese_Chat_T5_Base/resolve/main/spiece.model
- Command line
-
hf download hf://mxmax/Chinese_Chat_T5_Base/spiece.model
-
curl -L -o spiece.model https://huggingface.co/mxmax/Chinese_Chat_T5_Base/resolve/main/spiece.model
742 kB
- Xet hash:
- 59354368bf706e399d904f5e0a96f03044d97d99b3d5ff269d1903e3064ddb9f
- Size of remote file:
- 742 kB
- SHA256:
- 5c2083a4dd8b56e99db4a408d68a50d4374252628247dbdc9d5931fddcf0a66d
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