Summarization
Transformers
PyTorch
English
bart
text2text-generation
sagemaker
Eval Results (legacy)
Instructions to use philschmid/bart-base-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/bart-base-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-base-samsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("philschmid/bart-base-samsum") model = AutoModelForSeq2SeqLM.from_pretrained("philschmid/bart-base-samsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
3456945 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:7ce1e4b47d7e2bf2d0c8b8757cb9b372beec5d3906ba7d3437ae751ffd3c50ab
size 2351
|