{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"hf-model-facebook--bart-large-xsum","slug":"facebook--bart-large-xsum","name":"bart-large-xsum","type":"model","url":"https://huggingface.co/facebook/bart-large-xsum","page_url":"https://unfragile.ai/facebook--bart-large-xsum","categories":["data-analysis"],"tags":["transformers","pytorch","tf","jax","rust","bart","text2text-generation","summarization","en","arxiv:1910.13461","license:mit","model-index","endpoints_compatible","deploy:azure","region:us"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"hf-model-facebook--bart-large-xsum__cap_0","uri":"capability://text.generation.language.abstractive.summarization.generation","name":"abstractive summarization generation","description":"This capability utilizes the BART architecture, which employs a sequence-to-sequence model with a transformer backbone, allowing it to generate concise summaries from longer texts by understanding context and semantics. It leverages pre-training on large datasets followed by fine-tuning on specific summarization tasks, making it adept at producing coherent and contextually relevant outputs. The model's architecture allows for flexible input lengths and can handle various text formats effectively.","intents":["How can I generate a summary for a long research paper?","Can I create concise summaries for multiple articles at once?","What is the best way to summarize meeting notes into key points?"],"best_for":["content creators needing quick summaries of large texts","researchers summarizing academic papers","business professionals condensing reports"],"limitations":["May struggle with highly technical or domain-specific jargon","Output quality can vary based on input complexity","Limited to English and specific training data"],"requires":["Python 3.6+","Transformers library version 4.0+","Access to Hugging Face model hub"],"input_types":["text"],"output_types":["text"],"categories":["text-generation-language","nlp-tools"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":32,"verified":false,"data_access_risk":"low","permissions":["Python 3.6+","Transformers library version 4.0+","Access to Hugging Face model hub"],"failure_modes":["May struggle with highly technical or domain-specific jargon","Output quality can vary based on input complexity","Limited to English and specific training data","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.3760260895805505,"quality":0.12,"ecosystem":0.5000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.35,"quality":0.2,"ecosystem":0.1,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:22.765Z","last_scraped_at":"2026-05-03T14:22:54.515Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":12085,"model_likes":36}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=facebook--bart-large-xsum","compare_url":"https://unfragile.ai/compare?artifact=facebook--bart-large-xsum"}},"signature":"+SMkSi+muA5x33GQsY3GDG/AxLD4f9bmz1iU3JPOpVjoxxfdmFkoU3zHA5vA8YE57VruRwR+K2l4DsVso32VCw==","signedAt":"2026-06-22T22:26:58.408Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/facebook--bart-large-xsum","artifact":"https://unfragile.ai/facebook--bart-large-xsum","verify":"https://unfragile.ai/api/v1/verify?slug=facebook--bart-large-xsum","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}