Instructions to use krm/BARTkrame-abstract with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krm/BARTkrame-abstract 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")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("krm/BARTkrame-abstract") model = AutoModelForSeq2SeqLM.from_pretrained("krm/BARTkrame-abstract", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training good 2
Browse files
pytorch_model.bin
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runs/Oct15_06-02-26_1243a7efd2f2/events.out.tfevents.1665814567.1243a7efd2f2.68.0
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