Summarization
Transformers
PyTorch
TensorFlow
German
t5
text2text-generation
text-generation-inference
Instructions to use ml6team/mt5-small-german-finetune-mlsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ml6team/mt5-small-german-finetune-mlsum 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="ml6team/mt5-small-german-finetune-mlsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ml6team/mt5-small-german-finetune-mlsum") model = AutoModelForSeq2SeqLM.from_pretrained("ml6team/mt5-small-german-finetune-mlsum") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#3 opened about 3 years ago
by
SFconvertbot
Better results than the reported results and some questions about the model
#2 opened almost 4 years ago
by
JingFan
Fine tune this model on my Corpus(German lang)
#1 opened almost 4 years ago
by
SudhanshuBlaze