Instructions to use dtruong46me/train-bart-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtruong46me/train-bart-base 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="dtruong46me/train-bart-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtruong46me/train-bart-base") model = AutoModelForSeq2SeqLM.from_pretrained("dtruong46me/train-bart-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ec96f17eb1803bd79d47a124aeea2ace1a02c694aa283b32ad853b197147b5e
- Size of remote file:
- 5.05 kB
- SHA256:
- b46736b6c37cf283cb011ede6b35ac875d308f168fba1891bf6f310fa33b729e
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