Instructions to use sshleifer/distilbart-xsum-12-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/distilbart-xsum-12-3 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="sshleifer/distilbart-xsum-12-3")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/distilbart-xsum-12-3") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/distilbart-xsum-12-3") - Notebooks
- Google Colab
- Kaggle
Addition of Rust model
#2
by schneiderfelipe - opened
- rust_model.ot +3 -0
rust_model.ot
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version https://git-lfs.github.com/spec/v1
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oid sha256:2271c87823d53cfee158c8de7b9a8d73ec8d721ea02e8994c888b24da5d888d3
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size 716310211
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