Summarization
Transformers
PyTorch
TensorBoard
ONNX
Safetensors
German
bart
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use Shahm/bart-german with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shahm/bart-german 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="Shahm/bart-german")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Shahm/bart-german") model = AutoModelForSeq2SeqLM.from_pretrained("Shahm/bart-german") - Notebooks
- Google Colab
- Kaggle
Update model tags to make the model more discoverable
#1
by dennlinger - opened
Hi there!
I've been looking for German summarization models recently, and only came across your fine-tuned model by accident.
The updates should make it more discoverable, since it is now possible to filter both for "German", as well as adding it to the "summarization" subset of models.
Best,
Dennis
Hi Dennis!
Thanks for your edits. i hope you will have fun using the model.
Best,
Shahm
Shahm changed pull request status to merged