Instructions to use Vino1502/scihigh-2026-task2-bart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vino1502/scihigh-2026-task2-bart 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="Vino1502/scihigh-2026-task2-bart")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Vino1502/scihigh-2026-task2-bart") model = AutoModelForSeq2SeqLM.from_pretrained("Vino1502/scihigh-2026-task2-bart", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 727a5a6aba4d8c85fc340c375b501659c705c0272d0410eb4b6ffa7c1b03da3a
- Size of remote file:
- 5.39 kB
- SHA256:
- d2ff782c8c44fa46e7e2218a88d3cc95106b73f6e74ca1c8adc5adf2bfb42110
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