e5-mistral-7b-instruct
Improving Text Embeddings with Large Language Models. Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, Furu Wei, arXiv 2024
Params
7.1 B
Context
32,768
Downloads 30d
424 K
Likes
569
Download history
daily snapshots · 56 days
▲ 218 K in the last 30 days (33.9%)
630 K424 K
Aug 23Sep 2Sep 12Sep 21
694 K420 K
Jul 28Aug 15Sep 3Sep 21
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f16 | 14.2 GB | 17.2 GB | ✅ Runs comfortably |
| model.safetensors (bf16, full) | bf16 + 32K ctx | 14.2 GB | 20.4 GB | ⚠️ Tight — reduce context |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- MistralModel
- Parameters
- 7.1 B
- Tensor type
- F16
- Context length
- 32,768
- Vocabulary
- 32,000
- Layers / heads
- 32 / 32
- Licence
- mit
- First seen on the Hub
- 2023-12-20
- Training datasets
- undisclosed
- MTEB ATEC (reported)
- 42.657334751856
- MTEB AFQMC (reported)
- 38.709750161904
- MTEB AmazonPolarityClassification (reported)
- 95.904856347086
- MTEB AmazonReviewsClassification (de) (reported)
- 52.156230111545
- MTEB AmazonReviewsClassification (en) (reported)
- 55.312119958151
- MTEB AmazonReviewsClassification (es) (reported)
- 49.195023008878
- MTEB AmazonReviewsClassification (fr) (reported)
- 48.434470184108
- MTEB AmazonReviewsClassification (ja) (reported)
- 48.686
- MTEB AmazonCounterfactualClassification (de) (reported)
- 72.143882579058
- MTEB AmazonCounterfactualClassification (en) (reported)
- 72.372077035326
- MTEB AmazonCounterfactualClassification (ja) (reported)
- 63.877335968499
- MTEB AmazonCounterfactualClassification (en-ext) (reported)
- 64.810929544507
- Added to our catalog
- 2026-07-28
Family
Base model and the most-downloaded derivatives in the catalog.
Compare with any feature-extraction model