Instructions to use mrm8488/bert2bert_shared-spanish-finetuned-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/bert2bert_shared-spanish-finetuned-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/bert2bert_shared-spanish-finetuned-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert2bert_shared-spanish-finetuned-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/bert2bert_shared-spanish-finetuned-summarization") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b8dd27ae55494c3722d976549f488b209287435b905c101b06549e9a8345f36
- Size of remote file:
- 2.54 kB
- SHA256:
- ffa6d35038ae0a6aedddb5799f79f14a389db4cdb03627144bc7e6a3468d0ae1
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