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Collections including paper arxiv:2403.20041

transformer-techniques

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2, 2024 • 104
Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs

Paper • 2403.20041 • Published Mar 29, 2024 • 34
ViTAR: Vision Transformer with Any Resolution

Paper • 2403.18361 • Published Mar 27, 2024 • 52

Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs

Paper • 2403.20041 • Published Mar 29, 2024 • 34

Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs

Paper • 2403.20041 • Published Mar 29, 2024 • 34

Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs

Paper • 2403.20041 • Published Mar 29, 2024 • 34
Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs

Paper • 2406.10209 • Published Jun 14, 2024 • 8

general pupose llm

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9.03k

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AI Comic Factory

Create your own AI comic with a single prompt
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22

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Mistral PDF Chat
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196

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Arxiv CS RAG

Ask an LLM about Arxiv papers
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58

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Mistral-7B

LLM, chatbot

Simple and Scalable Strategies to Continually Pre-train Large Language Models

Paper • 2403.08763 • Published Mar 13, 2024 • 49
Jamba: A Hybrid Transformer-Mamba Language Model

Paper • 2403.19887 • Published Mar 28, 2024 • 104
Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs

Paper • 2403.20041 • Published Mar 29, 2024 • 34
Advancing LLM Reasoning Generalists with Preference Trees

Paper • 2404.02078 • Published Apr 2, 2024 • 44

Memory efficient training

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Paper • 2403.03507 • Published Mar 6, 2024 • 183
Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs

Paper • 2403.20041 • Published Mar 29, 2024 • 34

Interesting things.

AtP*: An efficient and scalable method for localizing LLM behaviour to components

Paper • 2403.00745 • Published Mar 1, 2024 • 12
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 605
MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT

Paper • 2402.16840 • Published Feb 26, 2024 • 23
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Paper • 2402.13753 • Published Feb 21, 2024 • 114

Beyond Language Models: Byte Models are Digital World Simulators

Paper • 2402.19155 • Published Feb 29, 2024 • 49
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29, 2024 • 52
VisionLLaMA: A Unified LLaMA Interface for Vision Tasks

Paper • 2403.00522 • Published Mar 1, 2024 • 44
Resonance RoPE: Improving Context Length Generalization of Large Language Models

Paper • 2403.00071 • Published Feb 29, 2024 • 22

daily_paper_coll

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29, 2024 • 52
Beyond Language Models: Byte Models are Digital World Simulators

Paper • 2402.19155 • Published Feb 29, 2024 • 49
StarCoder 2 and The Stack v2: The Next Generation

Paper • 2402.19173 • Published Feb 29, 2024 • 136
Simple linear attention language models balance the recall-throughput tradeoff

Paper • 2402.18668 • Published Feb 28, 2024 • 18

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