Instructions to use mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization 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="mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42ed6643e0b07403f0366ed8c5bc821059d825f3d7f2ecbb4b9343e227c0eaf3
- Size of remote file:
- 2.03 kB
- SHA256:
- 44c10ac720f9d67bfa118693c4598a3f795d672c4541cf988b1f59096d47d500
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