Task
Feature Extraction
E
intfloat/e5-mistral-7b-instruct
Feature Extraction·intfloat· 412.8K· 567
sentence-transformers
mit
Feature Extraction
7.1B params
arxiv:2401.00368arxiv:2104.08663arxiv:2210.07316arxiv:2212.03533
Improving Text Embeddings with Large Language Models. Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, Furu Wei, arXiv 2024
# pull & run locally
pip install mlforge-sdk && mlforge pull intfloat/e5-mistral-7b-instruct
pip install mlforge-sdk && mlforge pull intfloat/e5-mistral-7b-instruct
Model details
Provider
intfloat
Framework
sentence-transformers
Parameters
7.1B
Size
27 GB
License
mit
Downloads
412.8K
Likes
567
Paper
arXiv:2401.00368
Updated
2026-04-02
About intfloat/e5-mistral-7b-instruct
--- tags: - mteb - sentence-transformers - transformers model-index: - name: e5-mistral-7b-instruct results: - task: type: STS dataset: type: C-MTEB/AFQMC name: MTEB AFQMC config: default split: validation revision: None metrics: - type: cossimpearson value: 37.863226091673866 - type: cossimspearman value: 38.98733013335281 - type: euclideanpearson value: 37.51783380497874 - type: euclideanspearman value: 38.98733012753365 - type: manhattanpearson value: 37.26706888081721 - type: manhattanspearman value: 38.709750161903834 - task: type: STS dataset: type: C-MTEB/ATEC name: MTEB ATEC config: default split: test revision: None metrics: - type: cossimpearson value: 43.33924583134623 - type: cossimspearman value: 42.84316155158754 - type: euclideanpearson value: 45.62709879515238 - type: euclideanspearman value: 42.843155921732404 - type: manhattanpearson value: 45.4786950991229 - type: manhattanspearman value: 42.657334751855984 - task: type: Classification dataset: type: mteb/amazoncounterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 78.68656716417911 - type: ap value: 41.71522322900398 - type: f1 value: 72.37207703532552 - task: type: Classification dataset: