Instructions to use T-Systems-onsite/mt5-small-sum-de-en-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use T-Systems-onsite/mt5-small-sum-de-en-v2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" 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("summarization", model="T-Systems-onsite/mt5-small-sum-de-en-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("T-Systems-onsite/mt5-small-sum-de-en-v2") model = AutoModelForSeq2SeqLM.from_pretrained("T-Systems-onsite/mt5-small-sum-de-en-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add multilingual to the language tag (#1)
Browse files- Add multilingual to the language tag (7dfe4e295adfa21701984740d2f0220b0a95d569)
Co-authored-by: Loïck BOURDOIS <lbourdois@users.noreply.huggingface.co>
README.md
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language:
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- de
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- en
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license: cc-by-nc-sa-4.0
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tags:
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- summarization
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datasets:
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- cnn_dailymail
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- xsum
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language:
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- de
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- en
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- multilingual
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license: cc-by-nc-sa-4.0
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tags:
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- summarization
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datasets:
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- cnn_dailymail
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- xsum
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