# Salesforce/SFR-Embedding-2_R

Model from Hugging Face for feature extraction: Salesforce/SFR-Embedding-2_R · sentence transformers

## Facts

- Type: Embedding
- Task: feature-extraction
- Framework: sentence-transformers
- License: cc-by-nc-4.0 — cc-by-nc-4.0: commercial use is not permitted; non-commercial use and adaptations require attribution. (https://spdx.org/licenses/CC-by-nc-4.0.html)
- Source: https://huggingface.co/Salesforce/SFR-Embedding-2_R
- Hosting: unknown (no download location recorded)
- Files: 15 listed, none hosted here
- File counts: "listed" is every file in the source repository; only hosted files download from Hugging Bay, and the download plan lists the files it selects for one download, so its count can differ.
- Hosted here: availability unknown
- Full repo upstream: 14.2 GB
- Recommended file: 14.2 GB (3 files)
- Download: none recorded
- Per-file SHA-256: not available (no files hosted on Hugging Bay)
- Run-ready: no (Hugging Bay has not certified a run path for this model; hosted bytes are downloadable and hash-checkable only)
- Peer-assisted fallbacks: 0 verified, 0 pending review
- Downloads: 18020
- Stars: 95
- Card completeness: 96%

## Description

External Hugging Face catalog record for Salesforce/SFR-Embedding-2_R. Task: feature extraction. Library: sentence transformers. Languages: en. Includes 12 model-card evaluation signals. Popularity signal at import: 18,020 downloads and 95 likes.

## Model Card Facts

- Declared license: cc-by-nc-4.0
- Pipeline: feature-extraction
- Library: sentence-transformers
- Task categories: feature-extraction
- Languages: en
- Model-index entries: Salesforce/SFR-Embedding-2_R
- Evaluation signals: 12 model-card eval results
- File hints: 15 upstream file samples

## Evaluation Signals

- MTEB AmazonCounterfactualClassification (en): accuracy = 92.71641791044776 (Classification)
- MTEB AmazonCounterfactualClassification (en): ap = 69.47931007147756 (Classification)
- MTEB AmazonCounterfactualClassification (en): f1 = 88.0252625393374 (Classification)
- MTEB AmazonPolarityClassification: accuracy = 97.31075 (Classification)
- MTEB AmazonPolarityClassification: ap = 96.26693923450127 (Classification)
- MTEB AmazonPolarityClassification: f1 = 97.31042448894502 (Classification)
- MTEB AmazonReviewsClassification (en): accuracy = 61.040000000000006 (Classification)
- MTEB AmazonReviewsClassification (en): f1 = 60.78646832640785 (Classification)
- MTEB ArguAna: map_at_1 = 37.767 (Retrieval)
- MTEB ArguAna: map_at_10 = 53.908 (Retrieval)

## File Hints

- .gitattributes (1.5 KB)
- 1_Pooling/config.json (297 B)
- README.md (54 KB)
- config.json (663 B)
- config_sentence_transformers.json (205 B)
- model-00001-of-00003.safetensors (4.6 GB) LFS
- model-00002-of-00003.safetensors (4.7 GB) LFS
- model-00003-of-00003.safetensors (4.0 GB) LFS
- model.safetensors.index.json (22 KB)
- modules.json (229 B)
- sentence_bert_config.json (54 B)
- special_tokens_map.json (624 B)

## Quality Checklist

- Summary: passed
- Description: passed
- Model card metadata: passed
- License: review
- Provenance: passed
- File inventory: passed
- Hosted bytes: passed
- Scan result: passed
- Manifest signature: pending

## Safety Notes

- External catalog metadata imported from Hugging Face public API on 2026-09-21T08:54:28.629Z.
- Upstream license: cc-by-nc-4.0. Mirror admission policy: permissive (owner policy; no license rights inferred).
- Model-index metadata found for Salesforce/SFR-Embedding-2_R.
- Not locally hosted, mirrored, signed, or rescanned by Hugging Bay.
- Not a run kit: hosted, hash-checked bytes only; run readiness is not certified for this model yet.

## Actions

- Web: https://huggingbay.xyz/artifact/hf-model-salesforce-sfr-embedding-2-r
- Files API: https://huggingbay.xyz/api/artifacts/hf-model-salesforce-sfr-embedding-2-r/files?limit=100
- Metadata: https://huggingbay.xyz/api/artifacts/hf-model-salesforce-sfr-embedding-2-r/metadata.json
- Distribution: https://huggingbay.xyz/api/artifacts/hf-model-salesforce-sfr-embedding-2-r/distribution
- Manifest: not available until files are hosted and release checks pass.
- Request mirror: POST https://huggingbay.xyz/api/artifacts/hf-model-salesforce-sfr-embedding-2-r/mirror-request
- Submit peer fallback for review: POST https://huggingbay.xyz/api/artifacts/hf-model-salesforce-sfr-embedding-2-r/decentralized-fallbacks