Instructions to use MT-Distillation/s-eng-swe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MT-Distillation/s-eng-swe 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="MT-Distillation/s-eng-swe")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("MT-Distillation/s-eng-swe") model = AutoModelForSeq2SeqLM.from_pretrained("MT-Distillation/s-eng-swe", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from MT-Distillation/s-eng-swe: direct link, hf CLI and curl.
- Browser
- Download file 66 Bytes
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https://huggingface.co/MT-Distillation/s-eng-swe/resolve/main/README.md
- Command line
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hf download hf://MT-Distillation/s-eng-swe/README.md
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curl -L -o README.md https://huggingface.co/MT-Distillation/s-eng-swe/resolve/main/README.md
66 Bytes
metadata
license: mit
language:
- en
- sv
pipeline_tag: translation