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:
- 1550bd9f7034d297773fbb695919c98dd335c8488ce9ae8e67a4868585456f86
- Size of remote file:
- 1.2 GB
- SHA256:
- fa5244c26a0b3220f6a1eca49f3b6d311fb41a0f8024f3708477e48f1b15eb0a
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