Instructions to use ENLP/mrasp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ENLP/mrasp 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/mrasp", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ENLP/mrasp", trust_remote_code=True) model = AutoModel.from_pretrained("ENLP/mrasp", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
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## 一、项目介绍
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此项目是参考github上优秀的机器翻译项目[mRASP](https://github.com/linzehui/mRASP),将官方开源的fairseq预训练权重改写为transformers架构,使其能够更加方便使用。
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## 二、使用方法
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---
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tags:
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- translation
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license: apache-2.0
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metrics:
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- bleu
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- sacrebleu
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---
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## 一、项目介绍
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此项目是参考github上优秀的机器翻译项目[mRASP](https://github.com/linzehui/mRASP),将官方开源的fairseq预训练权重改写为transformers架构,使其能够更加方便使用。
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## 二、使用方法
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