Instructions to use microsoft/unihanlm-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/unihanlm-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/unihanlm-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("microsoft/unihanlm-base") model = AutoModel.from_pretrained("microsoft/unihanlm-base") - Notebooks
- Google Colab
- Kaggle
Add multilingual to the language tag
#1
by lbourdois - opened
README.md
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@@ -2,9 +2,10 @@
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language:
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- zh
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- ja
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tags:
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- crosslingual
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-
license: apache-2.0
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datasets:
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- Wikipedia
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---
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language:
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- zh
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- ja
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- multilingual
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license: apache-2.0
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tags:
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- crosslingual
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datasets:
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- Wikipedia
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---
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