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): a4f0c54
Update README.md
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README.md
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@@ -23,8 +23,8 @@ Sample generation script :
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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import torch
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device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
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tokenizer = transformers.AutoTokenizer.from_pretrained(
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model = AutoModelForSeq2SeqLM.from_pretrained(
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model.to(device)
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tokenizer.src_lang = "zh"
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tokenizer.tgt_lang = "en"
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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import torch
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device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
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tokenizer = transformers.AutoTokenizer.from_pretrained("CadenzaBaron/M2M100-418M-for-GameTranslation-Finetuned-Zh-En")
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model = AutoModelForSeq2SeqLM.from_pretrained("CadenzaBaron/M2M100-418M-for-GameTranslation-Finetuned-Zh-En")
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model.to(device)
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tokenizer.src_lang = "zh"
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tokenizer.tgt_lang = "en"
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