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_config.json from Shahm/bart-german: direct link, hf CLI and curl.
- Browser
- Download file 353 Bytes
-
https://huggingface.co/Shahm/bart-german/resolve/refs%2Fpr%2F13/tokenizer_config.json
- Command line
-
hf download hf://Shahm/bart-german@refs/pr/13/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Shahm/bart-german/resolve/refs%2Fpr%2F13/tokenizer_config.json
353 Bytes
| {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "add_prefix_space": false, "errors": "replace", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>", "trim_offsets": true, "model_max_length": 1024, "special_tokens_map_file": null, "name_or_path": "facebook/bart-base", "tokenizer_class": "BartTokenizer"} |