Cocom V1 128 Mistral 7b

🚀 COCOM模型 - 高效上下文壓縮助力問答生成

COCOM是一種有效的上下文壓縮方法，它能將長上下文縮減為少量的上下文嵌入，從而顯著加快問答生成速度。

📚 模型概述

COCOM是一種高效的上下文壓縮方法，可將長上下文壓縮為少量的上下文嵌入（Context Embeddings），極大地加快問答生成時間。

✨ 主要特性

高效的答案生成

檢索增強生成（RAG）通過外部上下文擴展輸入，克服了大語言模型知識有限的問題。然而，RAG的一個主要缺點是輸入越長，解碼時間顯著增加。我們提出的COCOM方法，作為一種有效的上下文壓縮方法，將長上下文壓縮為少量的上下文嵌入，從而加快生成時間。該方法允許不同的壓縮率，可在解碼時間和答案質量之間進行權衡。與早期方法相比，COCOM能更有效地處理多個上下文，顯著減少長輸入的解碼時間。與現有的高效上下文壓縮方法相比，我們的方法在實現高達5.69倍加速的同時，還能取得更高的性能。

📦 模型推理

對於批量處理，模型的輸入包括：

• questions (list)：包含問題的列表
• contexts (list of lists)：每個問題對應一個上下文列表，且每個問題的上下文數量固定。模型在微調（和推理）時使用 5 個上下文。

模型將問題壓縮為上下文嵌入，並根據提供的上下文嵌入回答問題。

💻 使用示例

基礎用法

from transformers import AutoModel

model = AutoModel.from_pretrained('naver/cocom-v1-128-mistral-7b', trust_remote_code=True)
model = model.to('cuda')
contexts = [[
  'Rosalind Bailey. Rosalind Bailey Rosalind Bailey (born 1946) is a British actress, known for her portrayal of Sarah Headley ("née" Lytton) in the 1970s and 1980s BBC television drama “When the Boat Comes In". Bailey has appeared in numerous British television drama series, including "Byker Grove", “Distant Shores" and "Burn Up". Her stage work includes playing Miss Mary Shepherd in Alan Bennett’s play "The Lady in the Van”.',
  'Malcolm Terris. Malcolm Terris Malcolm Terris (born 11 January 1941 in Sunderland, County Durham) is a British actor. He had a lengthy career in a large number of television programmes. Possibly his best-known role was in "When the Boat Comes In", a popular 1970s series, where he played the part of Matt Headley. His film career includes appearances in "The First Great Train Robbery" (1978), "McVicar" (1980), "The Plague Dogs" (1982, voice only), "Slayground" (1983), “The Bounty" (1984) as Thomas Huggan, ship’s surgeon, "Mata Hari" (1985), "Revolution" (1985), “Scandal" (1989), and “Chaplin” (1992). His TV appearances include: One episode of',
  'When the Boat Comes In. When the Boat Comes In When the Boat Comes In is a British television period drama produced by the BBC between 1976 and 1981. The series stars James Bolam as Jack Ford, a First World War veteran who returns to his poverty-stricken (fictional) town of Gallowshield in the North East of England. The series dramatises the political struggles of the 1920s and 1930s and explores the impact of national and international politics upon Ford and the people around him. Section:Production. The majority of episodes were written by creator James Mitchell, but in Series 1 north-eastern',
  'Susie Youssef. Youssef began her comedy career as a writer for "The Ronnie Johns Half Hour" in 2006, and made her acting debut in the short film "Clicked" in the role of Lina in 2011. In 2014, she played Jane in the short film "Kevin Needs to Make New Friends: Because Everyone Hates Him for Some Reason" and then turned to television where she appeared in "The Chaser’s Media Circus". In 2014, Youssef played the lead role of Sarah in the Hayloft Project’s stage play "The Boat People" which won the Best On Stage award at the FBi SMAC Awards',
  'Madelaine Newton. Madelaine Newton Madelaine Newton is a British actress best known for her portrayal of Dolly in 1970s BBC television drama "When the Boat Comes In". She is married to actor Kevin Whately, known for his role as Robert "Robbie" Lewis in both "Inspector Morse” and its spin-off "Lewis". They have two children. She starred alongside her husband in the “Inspector Morse" episode "Masonic Mysteries" as Beryl Newsome - the love-interest of Morse - whom Morse was wrongly suspected of murdering. She played Whately’s on-screen wife in the 1988 Look and Read children’s serial, Geordie Racer. She also made'
  ]]
questions = ['who played sarah hedley in when the boat comes in?']

answers = model.generate_from_text(contexts=contexts, questions=questions, max_new_tokens=128)

print(answers)

📖 參考文獻

• 論文：https://arxiv.org/pdf/2407.09252

@misc{rau2024contextembeddingsefficientanswer,
      title={Context Embeddings for Efficient Answer Generation in RAG}, 
      author={David Rau and Shuai Wang and Hervé Déjean and Stéphane Clinchant},
      year={2024},
      eprint={2407.09252},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2407.09252}, 
}