Instructions to use Azma-AI/bart-conversation-summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Azma-AI/bart-conversation-summarizer 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="Azma-AI/bart-conversation-summarizer")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Azma-AI/bart-conversation-summarizer") model = AutoModelForSeq2SeqLM.from_pretrained("Azma-AI/bart-conversation-summarizer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf26042b483fdeb254279bb4dbab794df3c1f46273bbfda91f942320107b3c10
- Size of remote file:
- 1.63 GB
- SHA256:
- 48c2a7c14073903e786d0299e4bc4d9b54ff68b64ecd6b022d30318c1748a1c9
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