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
Loading model via local config file
#5
by dparmar16 - opened
Due to a firewall issue, I cannot load in the model via the Hugging Face website configuration file. Currently it's loaded in like this:
from transformers import pipeline
summarizer = pipeline("summarization", model="philschmid/bart-large-cnn-samsum")
Is it possible to load in like this?
summarizer = pipeline("summarization", model="path_to_local_config_file.json")
You have to save the repository into a directory, e.g. distilbart/ and then you can do
summarizer = pipeline("summarization", model="distilbart/")
This is great, thank you! Can I just take the distilbart portion of the transformers repo? Or do I need to download the whole transformers repo?
What I'm seeing is here:
https://github.com/huggingface/transformers/tree/main/src/transformers/models/distilbert