Instructions to use CadenzaBaron/M2M100-418M-for-GameTranslation-Finetuned-Zh-En with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CadenzaBaron/M2M100-418M-for-GameTranslation-Finetuned-Zh-En 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="CadenzaBaron/M2M100-418M-for-GameTranslation-Finetuned-Zh-En")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CadenzaBaron/M2M100-418M-for-GameTranslation-Finetuned-Zh-En") model = AutoModelForSeq2SeqLM.from_pretrained("CadenzaBaron/M2M100-418M-for-GameTranslation-Finetuned-Zh-En") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 105abae
Update README.md
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README.md
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@@ -38,6 +38,8 @@ That being said, it has upsides for first MT pass in a game translation context
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2) It has basic cultivation/martial arts vocabulary
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3) Nothing is locked behind a paywall \o/
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Sample generation script :
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```python
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2) It has basic cultivation/martial arts vocabulary
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3) Nothing is locked behind a paywall \o/
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Note : Considering the dataset is built from the work of from modding groups (AMA and PoW Translation Team), who may not want their work to be reused for further AI training, it will not be made public nor shared.
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Sample generation script :
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```python
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