Instructions to use DS4H-ICTU/linguo_mt_ig_en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DS4H-ICTU/linguo_mt_ig_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="DS4H-ICTU/linguo_mt_ig_en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("DS4H-ICTU/linguo_mt_ig_en") model = AutoModelForSeq2SeqLM.from_pretrained("DS4H-ICTU/linguo_mt_ig_en") - Notebooks
- Google Colab
- Kaggle
Training complete
Browse files- README.md +5 -5
- model.safetensors +1 -1
README.md
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ig](https://huggingface.co/Helsinki-NLP/opus-mt-en-ig) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Bleu:
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Bleu |
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### Framework versions
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ig](https://huggingface.co/Helsinki-NLP/opus-mt-en-ig) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3984
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- Bleu: 7.8676
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Bleu |
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| 1.6893 | 1.0 | 625 | 1.5341 | 4.2257 |
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| 1.5707 | 2.0 | 1250 | 1.4315 | 6.8328 |
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| 1.4679 | 3.0 | 1875 | 1.3984 | 7.8676 |
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### Framework versions
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model.safetensors
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