Instructions to use krm/BARTkrame-abstract-mT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krm/BARTkrame-abstract-mT5 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="krm/BARTkrame-abstract-mT5")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("krm/BARTkrame-abstract-mT5") model = AutoModelForSeq2SeqLM.from_pretrained("krm/BARTkrame-abstract-mT5") - Notebooks
- Google Colab
- Kaggle
Training good 1
Browse files
pytorch_model.bin
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runs/Oct15_14-29-15_d7f3a3cc5832/events.out.tfevents.1665844233.d7f3a3cc5832.65.0
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runs/Oct15_14-29-15_d7f3a3cc5832/events.out.tfevents.1665846095.d7f3a3cc5832.65.2
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