# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("QuinineAlpha/bart_samsum")
model = AutoModelForSeq2SeqLM.from_pretrained("QuinineAlpha/bart_samsum", device_map="auto")Quick Links
bart_samsum
This model is a fine-tuned version of facebook/bart-large-xsum on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.4947
- Rouge1: 53.3294
- Rouge2: 28.6009
- Rougel: 44.2008
- Rougelsum: 49.2031
- Bleu: 0.0
- Meteor: 0.4887
- Gen Len: 30.1209
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Downloads last month
- 18
Model tree for QuinineAlpha/bart_samsum
Base model
facebook/bart-large-xsum
# 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="QuinineAlpha/bart_samsum")