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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1aeadace5aae48f9b6be6c9ed9be5680925e9aa6a1ad479200d5f03dfec14674
- Size of remote file:
- 3.12 kB
- SHA256:
- 027791caf2d9954be034792270961c6bc5af22ea31412c5e1b9de80e22226070
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