Instructions to use sshleifer/pegasus-cnn-ft-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/pegasus-cnn-ft-v2 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="sshleifer/pegasus-cnn-ft-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/pegasus-cnn-ft-v2") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/pegasus-cnn-ft-v2") - Notebooks
- Google Colab
- Kaggle
Update logs/test_rouge.json
Browse files- logs/test_rouge.json +1 -0
logs/test_rouge.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"rouge1": 44.1264, "rouge2": 21.3716, "rougeL": 30.9452, "n_obs": 11490, "runtime": 16097, "seconds_per_sample": 1.401}
|