Instructions to use Xmm/bart-large-entity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Xmm/bart-large-entity 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="Xmm/bart-large-entity")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Xmm/bart-large-entity") model = AutoModelForSeq2SeqLM.from_pretrained("Xmm/bart-large-entity") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8175052b0cf7f336ceb2e671fc3cff0484bd2127b025c020645692d479c3b2c
- Size of remote file:
- 3.9 kB
- SHA256:
- 2ebacc2bfe37ef4f2408c439429e67a92e14b1488d5b38c7429a21c86590a2bd
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