Instructions to use CLAck/en-km with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLAck/en-km 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="CLAck/en-km")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CLAck/en-km") model = AutoModelForSeq2SeqLM.from_pretrained("CLAck/en-km", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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- translation
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This model translate from English to Khmer.
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It is
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This is the result after 30 epochs of pure fine-tuning of khmer language.
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- translation
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This model translate from English to Khmer.
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It is the pure fine-tuned version of MarianMT model en-zh.
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This is the result after 30 epochs of pure fine-tuning of khmer language.
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