README.md

metadata

license: mit
language:
  - en
  - de
  - fr
  - es
  - zh
  - ja
  - ko
  - ar
  - hi
  - pt
  - ru
  - it
  - nl
  - pl
  - tr
  - vi
  - th
  - id
  - sv
  - da
  - 'no'
  - fi
  - cs
  - ro
  - hu
  - bg
  - uk
  - ca
  - el
  - hr
  - sk
  - sl
  - et
  - lt
  - lv
  - ms
  - tl
  - sw
  - af
  - cy
  - ga
  - sq
  - mk
  - bs
  - mt
  - gl
  - eu
  - is
  - ka
  - hy
  - kk
  - uz
  - az
  - be
  - mn
  - ne
  - si
  - km
  - my
  - lo
  - am
  - ps
  - sd
  - ku
  - ug
  - bo
  - dz
  - fy
tags:
  - embeddings
  - gguf
  - ggml
  - text-embeddings
  - bert
  - crispembed
  - ollama
pipeline_tag: feature-extraction
base_model: intfloat/multilingual-e5-small

multilingual-e5-small GGUF

GGUF format of intfloat/multilingual-e5-small for use with CrispEmbed and Ollama.

Files

File	Quantization	Size
multilingual-e5-small-q4_k.gguf	Q4_K	0 MB
multilingual-e5-small-q8_0.gguf	Q8_0	0 MB
multilingual-e5-small.gguf	F32	0 MB

Recommended: Q8_0 for quality (cos vs HF: 0.9999), Q4_K for size (0.990).

Quick Start

CrispEmbed

./crispembed -m multilingual-e5-small "Hello world"
./crispembed-server -m multilingual-e5-small --port 8080

Ollama (with CrispStrobe fork)

# Create model
echo "FROM multilingual-e5-small-q8_0.gguf" > Modelfile
ollama create multilingual-e5-small -f Modelfile

# Embed
curl http://localhost:11434/api/embed -d '{"model":"multilingual-e5-small","input":["Hello world"]}'

Python (CrispEmbed)

from crispembed import CrispEmbed
model = CrispEmbed("multilingual-e5-small-q8_0.gguf")
vectors = model.encode(["Hello world", "Goodbye world"])

Model Details

Property	Value
Architecture	BERT
Parameters	118M
Embedding Dimension	384
Layers	12
Pooling	mean
Tokenizer	SentencePiece
Language	multilingual
Q8_0 vs HuggingFace	0.9999
Q4_K vs HuggingFace	0.990

Server API

CrispEmbed server supports four API dialects:

• POST /embed — native
• POST /v1/embeddings — OpenAI-compatible
• POST /api/embed — Ollama-compatible
• POST /api/embeddings — Ollama legacy

Credits

• Original model: intfloat/multilingual-e5-small
• Inference: CrispEmbed (MIT, ggml-based)