Instructions to use Binaryy/bart-base-finetuned-findsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Binaryy/bart-base-finetuned-findsum 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="Binaryy/bart-base-finetuned-findsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Binaryy/bart-base-finetuned-findsum") model = AutoModelForSeq2SeqLM.from_pretrained("Binaryy/bart-base-finetuned-findsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3cff7a20f1d1a74514fcc7d630540fb7d264abd096e9846be906c017ae6df4e
- Size of remote file:
- 5.11 kB
- SHA256:
- 9e4344689fd7f933d1af36684672db103bb28773484a477c8ed8da3b33d72a3f
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