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")# pip install -U transformers accelerate # 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
Adding ONNX file of this model (#3)
Browse files- Adding ONNX file of this model (b95d8bc170a686f5e519ce8ad1679f7f1cd37669)
Co-authored-by: Ken Cheng <Ken22333@users.noreply.huggingface.co>
- model.onnx +3 -0
model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:e6f824363408023997c31ad654afab61a88033553ade1789d361b1fb6fcdc775
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size 712695682
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