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
Download tokenizer.json from Shahm/bart-german: direct link, hf CLI and curl.
- Browser
- Download file 1.36 MB
-
https://huggingface.co/Shahm/bart-german/resolve/refs%2Fpr%2F4/tokenizer.json
- Command line
-
hf download hf://Shahm/bart-german@refs/pr/4/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Shahm/bart-german/resolve/refs%2Fpr%2F4/tokenizer.json
1.36 MB
File too large to display, you can check the raw version instead.