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:
# 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") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -58,7 +58,7 @@ from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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tokenizer = AutoTokenizer.from_pretrained("mxmax/Chinese_Chat_T5_Base")
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model = AutoModelForSeq2SeqLM.from_pretrained("mxmax/Chinese_Chat_T5_Base")
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device = 'cuda' if cuda.is_available() else 'cpu'
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def postprocess(text):
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return text.replace(".", "").replace('</>','')
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tokenizer = AutoTokenizer.from_pretrained("mxmax/Chinese_Chat_T5_Base")
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model = AutoModelForSeq2SeqLM.from_pretrained("mxmax/Chinese_Chat_T5_Base")
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device = 'cuda' if cuda.is_available() else 'cpu'
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model.to(device)
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def postprocess(text):
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return text.replace(".", "").replace('</>','')
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