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
- Xet hash:
- ea2a13f97a83c9b8b850e2cc48a819a5dd5668431d0fa7dd42ffa00e2401c444
- Size of remote file:
- 1.2 GB
- SHA256:
- 6f57f9048716964bfa95a08fe021d5a8c439f369e04533f6b3865fb755a3173f
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