# 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")Quick Links
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Evaluation results
- Validation ROGUE-1 on SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarizationself-reported54.876
- Validation ROGUE-2 on SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarizationself-reported29.6869,
- Validation ROGUE-L on SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarizationself-reported44.987
- loss on SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarizationself-reported1.478
# 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")