# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("sesar/BartLargeCNN-FineTuned")
model = AutoModelForSeq2SeqLM.from_pretrained("sesar/BartLargeCNN-FineTuned")Quick Links
BartLargeCNN-FineTuned
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
Training results
Framework versions
- Transformers 4.29.2
- TensorFlow 2.12.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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# 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="sesar/BartLargeCNN-FineTuned")