mistral-7b-instruct-v0-2-b820eb94·3 events·first seen Aliases: Mistral 7B Instruct v0.2, Mistral 7B Instruct, Mistral-7B-Instruct-v0.3
A new arXiv preprint investigates whether LLMs exhibit a functional analog to the psycholinguistic production-perception distinction, using direct token probability measurements rather than metalinguistic prompting. Using Llama-3.1-8B and four other open-weight models, the authors find that production-perception prompt distances consistently exceed production-production distances by a ratio of ~1.8, with near-ceiling correlations in the production-production control confirming the effect is specific to communicative framing. The effect replicates across five models spanning base and instruction-tuned variants, and temporal analysis shows perception prompts exert strongest influence at sequence beginnings. The findings suggest prompt framing alone induces a production-perception distinction in decoder-only architectures.
Mistral AI released Mistral 7B, a 7.3B parameter language model under the Apache 2.0 license that outperforms Llama 2 13B across all evaluated benchmarks and approaches Llama 34B on many tasks. The model employs Grouped-Query Attention (GQA) for faster inference and Sliding Window Attention (SWA) to handle longer sequences at reduced cost, achieving roughly 2x speed improvement at 16k sequence length. A fine-tuned chat variant, Mistral 7B Instruct, outperforms all 7B chat models on MT-Bench and is competitive with 13B-class chat models. The release includes deployment support for AWS, GCP, Azure, HuggingFace, and local use via vLLM.
Mistral AI opened beta access to its first developer platform, La Plateforme, offering three generative text endpoints (mistral-tiny, mistral-small, mistral-medium) and an embedding endpoint. Mistral-tiny serves Mistral 7B Instruct v0.2, mistral-small serves Mixtral 8x7B, and mistral-medium serves an unreleased prototype model scoring 8.6 on MT-Bench. The platform also introduces Mistral-embed with a 1024-dimension embedding model achieving 55.26 on MTEB. The API follows OpenAI-compatible chat interface specifications and is ramping toward general availability.