Translation
Transformers
PyTorch
English
Chinese
mbart
text2text-generation
fine tune
fine_tune
mbart-50
Instructions to use Normal1919/mbart-large-50-one-to-many-lil-fine-tune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Normal1919/mbart-large-50-one-to-many-lil-fine-tune 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="Normal1919/mbart-large-50-one-to-many-lil-fine-tune")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Normal1919/mbart-large-50-one-to-many-lil-fine-tune") model = AutoModelForSeq2SeqLM.from_pretrained("Normal1919/mbart-large-50-one-to-many-lil-fine-tune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 83e5bd9
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README.md
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I {i}should{/i} say that I feel a little relieved to find out that
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{i}this{/i} is why you’ve been hanging out with Kaori lately, though. She’s
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really pretty and I got jealous and...I’m sorry.
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pipeline_tag: translation
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- fine tune
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inference:
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parameters:
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src_lang: en_XX
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tgt_lang: zh_CN
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widget:
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- text: >-
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I {i}should{/i} say that I feel a little relieved to find out that
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{i}this{/i} is why you’ve been hanging out with Kaori lately, though. She’s
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really pretty and I got jealous and...I’m sorry.
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pipeline_tag: translation
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