Instructions to use ENLP/mrasp2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ENLP/mrasp2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="ENLP/mrasp2", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ENLP/mrasp2", trust_remote_code=True) model = AutoModel.from_pretrained("ENLP/mrasp2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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该模型支持32种语言,更多详细参考[mRASP2](https://github.com/PANXiao1994/mRASP2),此模型库的tokenizer仅针对中英双语进行优化,如果需要使用其他语言请
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自行参考tokenization_bat.py进行修改。请注意,这是官方的6e6d-no-mono模型,12e12d两个模型暂时无法实现,找不到原因,如果有知道的小伙伴可以分享出来。
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## 四、其他模型
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该模型支持32种语言,更多详细参考[mRASP2](https://github.com/PANXiao1994/mRASP2),此模型库的tokenizer仅针对中英双语进行优化,如果需要使用其他语言请
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自行参考tokenization_bat.py进行修改。请注意,这是官方的6e6d-no-mono模型,12e12d两个模型暂时无法实现,找不到原因,如果有知道的小伙伴可以分享出来。
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## 四、其他模型
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[ENLP/mrasp](https://huggingface.co/ENLP/mrasp)
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