Summarization
Transformers
TensorBoard
Safetensors
encoder-decoder
text2text-generation
Generated from Trainer
Instructions to use folflo/Bert2Bert_m_m_finetined_on_HunSum_1201 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use folflo/Bert2Bert_m_m_finetined_on_HunSum_1201 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="folflo/Bert2Bert_m_m_finetined_on_HunSum_1201")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("folflo/Bert2Bert_m_m_finetined_on_HunSum_1201") model = AutoModelForSeq2SeqLM.from_pretrained("folflo/Bert2Bert_m_m_finetined_on_HunSum_1201", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed17a29e31eb3d117e6e8ff0499a5733c97e57557b623dc2f7247443d4baaa52
- Size of remote file:
- 6.26 kB
- SHA256:
- 0ebbd544243deacfae48f2ed29a9147c990545bf82a34d3d410f7857bcc4ce89
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