Instructions to use google/pegasus-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/pegasus-large 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="google/pegasus-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/pegasus-large") model = AutoModelForSeq2SeqLM.from_pretrained("google/pegasus-large") - Inference
- Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -1
config.json
CHANGED
|
@@ -35,7 +35,7 @@
|
|
| 35 |
},
|
| 36 |
"length_penalty": 0.8,
|
| 37 |
"max_length": 256,
|
| 38 |
-
"max_position_embeddings":
|
| 39 |
"model_type": "pegasus",
|
| 40 |
"normalize_before": true,
|
| 41 |
"normalize_embedding": false,
|
|
|
|
| 35 |
},
|
| 36 |
"length_penalty": 0.8,
|
| 37 |
"max_length": 256,
|
| 38 |
+
"max_position_embeddings": 1024,
|
| 39 |
"model_type": "pegasus",
|
| 40 |
"normalize_before": true,
|
| 41 |
"normalize_embedding": false,
|