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:
- 9aa247b9f497033c1a4506e9a4694436690d2273a49619148868145c99865975
- Size of remote file:
- 556 MB
- SHA256:
- 89f4c2315b8488562f05973339444b27022a7c92818a7bab4b053a01279189e5
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