Translation
Transformers
PyTorch
Safetensors
m2m_100
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use kazandaev/m2m100_418M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kazandaev/m2m100_418M 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="kazandaev/m2m100_418M")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kazandaev/m2m100_418M") model = AutoModelForSeq2SeqLM.from_pretrained("kazandaev/m2m100_418M") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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# m2m100_418M
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This model is a fine-tuned version of [kazandaev/m2m100_418M](https://huggingface.co/kazandaev/m2m100_418M) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.8954
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- Bleu: 32.0585
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# m2m100_418M
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This model is a fine-tuned version of [kazandaev/m2m100_418M](https://huggingface.co/kazandaev/m2m100_418M) on the custom en-ru dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8954
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- Bleu: 32.0585
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