Mistral 7B

2023/10/10 by Albert Q. Jiang, Alexandre Sablayrolles, Jiang, Albert Q. +35 · 5 voices · 549 citations
Computer Science · #Algorithm #Artificial intelligence #Code (set theory) #Computer science #Inference #License #MIT License #Machine Learning and Data Classification #Natural Language Processing Techniques #Operating system #Programming language #Sliding window protocol #Topic Modeling #Window (computing) #cs.AI #cs.CL #cs.LG

paper · pdf · doi:10.48550/arxiv.2310.06825

published in arXiv (Cornell University) (Cornell University)

openalex publication_date 2023/10/10 · openalex created_date 2023/10/12 · openalex updated_date 2026/08/05

Abstract

We introduce Mistral 7B v0.1, a 7-billion-parameter language model engineered for superior performance and efficiency. Mistral 7B outperforms Llama 2 13B across all evaluated benchmarks, and Llama 1 34B in reasoning, mathematics, and code generation. Our model leverages grouped-query attention (GQA) for faster inference, coupled with sliding window attention (SWA) to effectively handle sequences of arbitrary length with a reduced inference cost. We also provide a model fine-tuned to follow instructions, Mistral 7B -- Instruct, that surpasses the Llama 2 13B -- Chat model both on human and automated benchmarks. Our models are released under the Apache 2.0 license.

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• Should LLM Safety Be More Than Refusing Harmful Instructions?
• Adaptive Task Vectors for Large Language Models
• Truth over Tricks: Measuring and Mitigating Shortcut Learning in Misinformation Detection
• MASTER: Enhancing Large Language Model via Multi-Agent Simulated Teaching
• CogniAlign: Word-Level Multimodal Speech Alignment with Gated Cross-Attention for Alzheimer's Detection
• StochasTok: Improving Fine-Grained Subword Understanding in LLMs
• Reasoning-Based Approach with Chain-of-Thought for Alzheimer's Detection Using Speech and Large Language Models
• SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
• SPACE: Your Genomic Profile Predictor is a Powerful DNA Foundation Model
• SynPO: Synergizing Descriptiveness and Preference Optimization for Video Detailed Captioning
• Compress, Gather, and Recompute: REFORMing Long-Context Processing in Transformers
• Earley-Driven Dynamic Pruning for Efficient Structured Decoding
• Keeping an Eye on LLM Unlearning: The Hidden Risk and Remedy
• A Simple Linear Patch Revives Layer-Pruned Large Language Models
• Interpretable phenotyping of Heart Failure patients with Dutch discharge letters
• Cross-Attention Speculative Decoding
• Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration
• A Multi‑Region Brain Model to Elucidate the Role of Hippocampus in Spatially Embedded Decision‑Making
• Spoken Language Modeling with Duration-Penalized Self-Supervised Units
• From Parameters to Prompts: Understanding and Mitigating the Factuality Gap between Fine-Tuned LLMs
• GenIC: An LLM-Based Framework for Instance Completion in Knowledge Graphs
• Proximalized Preference Optimization for Diverse Feedback Types: A Decomposed Perspective on DPO
• Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs
• Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images
• Re-ttention: Ultra Sparse Visual Generation via Attention Statistical Reshape
• Bayesian Attention Mechanism: A Probabilistic Framework for Positional Encoding and Context Length Extrapolation
• Adaptive Detoxification: Safeguarding General Capabilities of LLMs through Toxicity-Aware Knowledge Editing
• Mustafar: Promoting Unstructured Sparsity for KV Cache Pruning in LLM Inference
• Spa-VLM: Stealthy Poisoning Attacks on RAG-based VLM
• Look Within or Look Beyond? A Theoretical Comparison Between Parameter-Efficient and Full Fine-Tuning
• RelationalFactQA: A Benchmark for Evaluating Tabular Fact Retrieval from Large Language Models
• Emotion-aware Dual Cross-Attentive Neural Network with Label Fusion for Stance Detection in Misinformative Social Media Content
• EntroLLM: Entropy Encoded Weight Compression for Efficient Large Language Model Inference on Edge Devices
• Can Large Language Models Predict Audio Effects Parameters from Natural Language?
• Efficient Large Language Model Inference with Neural Block Linearization
• Pretrained LLMs Learn Multiple Types of Uncertainty
• Incentivizing Inclusive Contributions in Model Sharing Markets
• ResSVD: Residual Compensated SVD for Large Language Model Compression
• SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection
• DoctorAgent-RL: A Multi-Agent Collaborative Reinforcement Learning System for Multi-Turn Clinical Dialogue
• The Role of Diversity in In-Context Learning for Large Language Models
• Correlating instruction-tuning (in multimodal models) with vision-language processing (in the brain)
• Adaptive Classifier-Free Guidance via Dynamic Low-Confidence Masking
• MA-RAG: Multi-Agent Retrieval-Augmented Generation via Collaborative Chain-of-Thought Reasoning
• FairPO: Robust Preference Optimization for Fair Multi-Label Learning
• WINA: Weight Informed Neuron Activation for Accelerating Large Language Model Inference
• EnvSDD: Benchmarking Environmental Sound Deepfake Detection
• Rethinking the Understanding Ability across LLMs through Mutual Information
• NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research
• Benchmarking and Rethinking Knowledge Editing for Large Language Models
• Multilingual Question Answering in Low-Resource Settings: A Dzongkha-English Benchmark for Foundation Models
• ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation
• Do You Keep an Eye on What I Ask? Mitigating Multimodal Hallucination via Attention-Guided Ensemble Decoding
• Scaling Up Biomedical Vision-Language Models: Fine-Tuning, Instruction Tuning, and Multi-Modal Learning
• Misaligning Reasoning with Answers -- A Framework for Assessing LLM CoT Robustness
• RBench-V: A Primary Assessment for Visual Reasoning Models with Multi-modal Outputs
• Explain Less, Understand More: Jargon Detection via Personalized Parameter-Efficient Fine-tuning
• Transformer Copilot: Learning from The Mistake Log in LLM Fine-tuning
• Advancing LLM Safe Alignment with Safety Representation Ranking
• Feed-Forward Steering in Transformer Residual Dynamics
• Scalable Defense against In-the-wild Jailbreaking Attacks with Safety Context Retrieval
• Set-LLM: A Permutation-Invariant LLM
• Position: Agentic Systems Constitute a Key Component of Next-Generation Intelligent Image Processing
• Model Merging is Secretly Certifiable: Non-Vacuous Generalisation Bounds for Low-Shot Learning
• UltraEdit: Training-, Subject-, and Memory-Free Lifelong Editing in Language Models
• Rank-K: Test-Time Reasoning for Listwise Reranking
• Phonetic Perturbations Reveal Tokenizer-Rooted Safety Gaps in LLMs
• Fragments to Facts: Partial-Information Fragment Inference from LLMs
• Beyond Words: Multimodal LLM Knows When to Speak
• Text Generation Beyond Discrete Token Sampling
• Safety Alignment Can Be Not Superficial With Explicit Safety Signals
• RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning
• Benchmarking and Confidence Evaluation of LALMs For Temporal Reasoning
• Large Language Models and Their Applications in Roadway Safety and Mobility Enhancement: A Comprehensive Review
• MARGE: Improving Math Reasoning for LLMs with Guided Exploration
• Improving LLM Outputs Against Jailbreak Attacks with Expert Model Integration
• Fine-grained Contrastive Learning for ECG-Report Alignment with Waveform Enhancement
• Data-driven material screening of secondary and natural cementitious precursors
• RH-RAG: Trustworthy Long-Form Generation for Privacy-Constrained Settings
• Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
• Intrinsic Self-Correction in LLMs: Towards Explainable Prompting via Mechanistic Interpretability
• SpecEdge: Scalable Edge-Assisted Serving Framework for Interactive LLMs
• Delta Attention: Fast and Accurate Sparse Attention Inference by Delta Correction
• ReWiND: Language-Guided Rewards Teach Robot Policies without New Demonstrations
• GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning
• Can AI Freelancers Compete? Benchmarking Earnings, Reliability, and Task Success at Scale
• EdgeMM: Multi-Core CPU with Heterogeneous AI-Extension and Activation-aware Weight Pruning for Multimodal LLMs at Edge
• Real-Time Out-of-Distribution Failure Prevention via Multi-Modal Reasoning
• Adversarial Attack on Large Language Models using Exponentiated Gradient Descent
• Visually Guided Decoding: Gradient-Free Hard Prompt Inversion with Language Models
• Multimodal Cancer Modeling in the Age of Foundation Model Embeddings
• JobHop: A Large-Scale Dataset of Career Trajectories
• Semantic Retention and Extreme Compression in LLMs: Can We Have Both?
• Reassessing Large Language Model Boolean Query Generation for Systematic Reviews
• Turning LLM Activations Quantization-Friendly
• Improving Block-Wise LLM Quantization by 4-bit Block-Wise Optimal Float (BOF4): Analysis and Variations
• Empowering Scientific Workflows with Federated Agents
• Latent Preference Coding: Aligning Large Language Models via Discrete Latent Codes
• Geometric Analysis of Token Selection in Multi-Head Attention
• TxP: Reciprocal Generation of Ground Pressure Dynamics and Activity Descriptions for Improving Human Activity Recognition
• Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach
• R-Bench: Graduate-level Multi-disciplinary Benchmarks for LLM & MLLM Complex Reasoning Evaluation
• SEval-Ex: A Statement-Level Framework for Explainable Summarization Evaluation
• Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency
• Advancing AI Research Assistants with Expert-Involved Learning
• Enhancing the Learning Experience: Using Vision-Language Models to Generate Questions for Educational Videos
• Cannot See the Forest for the Trees: Invoking Heuristics and Biases to Elicit Irrational Choices of LLMs
• Evaluating Vision Language Model Adaptations for Radiology Report Generation in Low-Resource Languages
• On the Limits of LLM Adaptability: Impact of Model-Internalized Priors on Annotation Task Performance
• LLMs can construct powerful representations and streamline sample-efficient supervised learning
• SpatialLLM: A Compound 3D-Informed Design towards Spatially-Intelligent Large Multimodal Models
• BrepCoder: A Unified Multimodal Large Language Model for Multi-task B-rep Reasoning
• Progressive Training for Explainable Citation-Grounded Dialogue: Reducing Hallucination to Zero in English-Hindi LLMs
• Precision Where It Matters: A Novel Spike Aware Mixed-Precision Quantization Strategy for LLaMA-based Language Models
• Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding
• Small or Large? Zero-Shot or Finetuned? Guiding Language Model Choice for Specialized Applications in Healthcare
• A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning
• DYNAMAX: Dynamic computing for Transformers and Mamba based architectures
• LLM Enhancer: Merged Approach using Vector Embedding for Reducing Large Language Model Hallucinations with External Knowledge
• Chain-of-Defensive-Thought: Structured Reasoning Elicits Robustness in Large Language Models against Reference Corruption
• HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation
• HiFloat4 Format for Language Model Inference
• BRIDGE: Benchmarking Large Language Models for Understanding Real-world Clinical Practice Text
• Online Safety Monitoring for LLMs
• Language-Critique Imitation Learning from Suboptimal Demonstrations
• Trait-space Monitoring for Emergent Misalignment During Supervised Finetuning
• MATCHA: Matching Text via Contrastive Semantic Alignment
• Transformer Scalability Crisis: The First Comprehensive Empirical Analysis of Performance Walls in Modern Language Models
• Structured Distillation for Personalized Agent Memory: 11x Token Reduction with Retrieval Preservation
• Zero-shot adaptable task planning for autonomous construction robots: a comparative study of lightweight single and multi-AI agent systems
• Knowledge-Driven Agentic Scientific Corpus Distillation Framework for Biomedical Large Language Models Training
• R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference
• Why Linear Interpretability Works: Invariant Subspaces as a Result of Architectural Constraints
• Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review
• AgentGate: A Lightweight Structured Routing Engine for the Internet of Agents
• Reversing Arrows in Large Language Models
• The Role of Open-Source LLMs in Shaping the Future of GeoAI
• CoheMark: A Novel Sentence-Level Watermark for Enhanced Text Quality
• MASR: Self-Reflective Reasoning through Multimodal Hierarchical Attention Focusing for Agent-based Video Understanding
• DataRx: Missingness-Aware Sampling for Safer Large Language Model Task-Specific Fine-Tuning
• Maglev: Sliding Recurrent Memory
• Revealing the Intrinsic Ethical Vulnerability of Aligned Large Language Models
• Language Models Are Implicitly Continuous
• Necessary, Decodable and Reversible, Yet Not Transferable: A Stress Test for Attention-Head Role Claims
• SHIELD: A Segmented Hierarchical Memory Architecture for Energy-Efficient LLM Inference on Edge NPUs
• Can Large Language Models Help Multimodal Language Analysis? MMLA: A Comprehensive Benchmark
• Generalized Neighborhood Attention: Multi-dimensional Sparse Attention at the Speed of Light
• Saliency-driven Dynamic Token Pruning for Large Language Models
• Vidi: Large Multimodal Models for Video Understanding and Editing
• MMInference: Accelerating Pre-filling for Long-Context VLMs via Modality-Aware Permutation Sparse Attention
• Fine-Tuning a 7B Advisor on Free-Tier GPUs: An Adapter-Handoff Recipe and a Synthetic-Data Reliability Caution
• Advancing Embodied Agent Security: From Safety Benchmarks to Input Moderation
• ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools
• Kuwain 1.5B: An Arabic SLM via Language Injection
• A Hierarchical Framework for Measuring Scientific Paper Innovation via Large Language Models
• Manipulating Multimodal Agents via Cross-Modal Prompt Injection
• A Data-Centric Approach for Safe and Secure Large Language Models against Threatening and Toxic Content
• Activated LoRA: Fine-tuned LLMs for Intrinsics
• Multilingual Contextualization of Large Language Models for Document-Level Machine Translation
• The Devil is in the Prompts: Retrieval-Augmented Prompt Optimization for Text-to-Video Generation
• Subitizing-Inspired_Large_Language_Models_for_Floorplanning
• Post-Hoc Trajectory-Risk Certification for Modular LLM-Based Security Agents
• A Dual-Space Framework for General Knowledge Distillation of Large Language Models
• The Scalability of Simplicity: Empirical Analysis of Vision-Language Learning with a Single Transformer
• HELIOS: Adaptive Model And Early-Exit Selection for Efficient LLM Inference Serving
• SilVar-Med: A Speech-Driven Visual Language Model for Explainable Abnormality Detection in Medical Imaging
• Learning from Reference Answers: Versatile Language Model Alignment without Binary Human Preference Data
• Do We Really Need Curated Malicious Data for Safety Alignment in Multi-modal Large Language Models?
• Improving In-Context Learning with Reasoning Distillation
• Alleviating the Fear of Losing Alignment in LLM Fine-tuning
• Large Language Models Could Be Rote Learners
• Jupiter: Fast and Resource-Efficient Collaborative Inference of Generative LLMs on Edge Devices
• Efficient Tuning of Large Language Models for Knowledge-Grounded Dialogue Generation
• LSR-MCTS: Alleviating Long Range Dependency in Code Generation
• LoRI: Reducing Cross-Task Interference in Multi-Task Low-Rank Adaptation
• ThoughtProbe: Classifier-Guided Thought Space Exploration Leveraging LLM Intrinsic Reasoning
• Alice: Proactive Learning with Teacher's Demonstrations for Weak-to-Strong Generalization
• ShadowCoT: Cognitive Hijacking for Stealthy Reasoning Backdoors in LLMs
• On the Impact of Language Nuances on Sentiment Analysis with Large Language Models: Paraphrasing, Sarcasm, and Emojis
• REVEAL: Relation-based Video Representation Learning for Video-Question-Answering
• Caption Anything in Video: Fine-grained Object-centric Captioning via Spatiotemporal Multimodal Prompting
• Generative Large Language Model usage in Smart Contract Vulnerability Detection
• Evaluating Knowledge Graph Based Retrieval Augmented Generation Methods under Knowledge Incompleteness
• How Social is It? A Benchmark for LLMs' Capabilities in Multi-user Multi-turn Social Agent Tasks
• Prompt Optimization with Logged Bandit Data
• Large language model for post‐earthquake structural damage assessment of buildings

Discussions

• Mistral 7B [hn, 267 points, 123 comments]
• Mistral 7B model [lemmy, 24 points, 8 comments]
• Here's a PDF containing the Mistral prompt: arxiv.org/pdf/2310.068... [bsky, 4 points, 1 comments]
• I started using it because it was one of the first open source models (for some contentious definition of open source) and it gave consistently good answers. Cracked team, just look at their paper. ar [bsky, 1 points, 1 comments]
• Here’s the documentation for Mistral 7B from a French LLM lab: arxiv.org/abs/2310.06825 [bsky, 0 points, 0 comments]

Related

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• LLaMA: Open and Efficient Foundation Language Models
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• GEB-1.3B: Open Lightweight Large Language Model
• Llama-Nemotron: Efficient Reasoning Models