Summarization
Transformers
PyTorch
TensorBoard
English
bart
text2text-generation
azureml
azure
codecarbon
Eval Results (legacy)
Instructions to use linydub/bart-large-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use linydub/bart-large-samsum 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="linydub/bart-large-samsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("linydub/bart-large-samsum") model = AutoModelForSeq2SeqLM.from_pretrained("linydub/bart-large-samsum") - Notebooks
- Google Colab
- Kaggle
| timestamp,experiment_id,project_name,duration,emissions,energy_consumed,country_name,country_iso_code,region,on_cloud,cloud_provider,cloud_region | |
| 2021-09-16T23:54:25,6d17f6b6-e3d1-4060-8b20-2ca43acf1f77,codecarbon,263.2430217266083,0.029715544634717518,0.09985062041235725,USA,USA,Washington,Y,azure,westus2 | |