Summarization
Transformers
PyTorch
English
bart
text2text-generation
sagemaker
Eval Results (legacy)
Instructions to use philschmid/bart-large-cnn-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/bart-large-cnn-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="philschmid/bart-large-cnn-samsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("philschmid/bart-large-cnn-samsum") model = AutoModelForSeq2SeqLM.from_pretrained("philschmid/bart-large-cnn-samsum") - Inference
- Notebooks
- Google Colab
- Kaggle
index out of range in self
#12
by andrewyang17 - opened
Hello,
I received an error saying "index out of range in self" when the input is large,
is there any configuration to overcome this?
instead of --
from transformers import pipeline
use:
from transformers import AutoModelForSeq2SeqLM
summarizer_pipeline = AutoModelForSeq2SeqLM.from_pretrained("philschmid/bart-large-cnn-samsum")
@pdahiya Can you send me the example to resolve this ?