Summarization
Transformers
PyTorch
Safetensors
Turkish
bart
text2text-generation
Eval Results (legacy)
Instructions to use mukayese/transformer-turkish-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mukayese/transformer-turkish-summarization 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="mukayese/transformer-turkish-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mukayese/transformer-turkish-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("mukayese/transformer-turkish-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3371c7d3f238dbda18243f25e42c9c90be9b4c0b315a2211d1b631fc535f3e9
- Size of remote file:
- 502 MB
- SHA256:
- 7cf1f1910ea0edc1b1d1c24684524e164efa9094f29ed2d84ec15b9340a5ff7a
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