
[2404.07979] LLoCO: Learning Long Contexts Offline - arXiv.org
Apr 11, 2024 · We propose LLoCO, a novel approach to address this problem by learning contexts offline through context compression and in-domain parameter-efficient finetuning with LoRA. Our method enables an LLM to create a concise representation of the original context and efficiently retrieve relevant information to answer questions accurately.
We propose LLoCO, a novel approach to ad-dress this problem by learning contexts offline through context compression and in-domain parameter-efficient finetuning with LoRA. Our method enables an LLM to create a concise representation of the original context and effi-ciently retrieve relevant information to answer questions accurately. Our ...
Paper page - LLoCO: Learning Long Contexts Offline - Hugging Face
Apr 12, 2024 · We introduce LLoCO, a technique that combines context compression, retrieval, and parameter-efficient finetuning using LoRA. Our approach extends the effective context window of a 4k token LLaMA2-7B model to handle up to 128k tokens.
B28 nuclear bomb - Wikipedia
The B28, originally Mark 28, was a thermonuclear bomb carried by U.S. tactical fighter bombers, attack aircraft and bomber aircraft. From 1962 to 1972 under the NATO nuclear weapons sharing program, American B28s also equipped six Europe-based Canadian CF-104 squadrons known as the RCAF Nuclear Strike Force.
LLoCO: Learning Long Contexts Offline - GitHub
LLoCO is a technique that learns documents offline through context compression and in-domain parameter-efficient finetuning using LoRA, which enables LLMs to handle long context efficiently. Setup a new environment and run: Use the following command to download the QuALITY dataset.
ECO B28 - Wikipedia
B28 is a chess opening that is classified by the ECO.<br\><br\>This opening classification refers to the following openings:<br\><br\> O'Kelly Variation, Sicilian; B28 (1.e4 c5 2.Nf3 a6) Kieseritzky System, Sicilian (1.e4 c5 2.Nf3 a6 3.b3)
We propose LLoCO, a novel approach to ad-dress this problem by learning contexts ofine through context compression and in-domain parameter-efcient netuning with LoRA. Our method enables an LLM to create a concise representation of the original context and ef-ciently retrieve relevant information to answer questions accurately. Our approach extends
LLoCO: Learning Long Contexts Offline - arXiv.org
Apr 11, 2024 · We introduce LLoCO, a technique that combines context compression, retrieval, and parameter-efficient finetuning using LoRA. Our approach extends the effective context window of a 4k token LLaMA2-7B model to handle up to 128k tokens.
LLOCO (@thereallloco) • Instagram photos and videos
21K Followers, 5,181 Following, 53 Posts - LLOCO (@thereallloco) on Instagram: "CEO of M.B.A.M ent Chi-Mia-Chi #LLKT #RIPSMYLEZ Chiraq,Drillinois Personal Page @donleco1"
21 January 1968 - This Day in Aviation
21 January 1968: A United States Air Force Boeing B-52G-100-BW Stratofortress, serial number 58-0188, assigned to the 380th Strategic Aerospace Wing, was flying an Airborne Nuclear Alert mission as part of Operation Chrome Dome. The bomber, call sign Hobo 28, had a crew of seven and was armed with four B28FI nuclear bombs carried in its bomb bay.