Instructions to use cstr/multilingual-e5-large-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use cstr/multilingual-e5-large-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf cstr/multilingual-e5-large-GGUF:IQ4_XS
# Run inference directly in the terminal:
llama cli -hf cstr/multilingual-e5-large-GGUF:IQ4_XS

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf cstr/multilingual-e5-large-GGUF:IQ4_XS
# Run inference directly in the terminal:
llama cli -hf cstr/multilingual-e5-large-GGUF:IQ4_XS

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf cstr/multilingual-e5-large-GGUF:IQ4_XS
# Run inference directly in the terminal:
./llama-cli -hf cstr/multilingual-e5-large-GGUF:IQ4_XS

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf cstr/multilingual-e5-large-GGUF:IQ4_XS
# Run inference directly in the terminal:
./build/bin/llama-cli -hf cstr/multilingual-e5-large-GGUF:IQ4_XS

Use Docker

docker model run hf.co/cstr/multilingual-e5-large-GGUF:IQ4_XS

LM Studio
Jan
Ollama
How to use cstr/multilingual-e5-large-GGUF with Ollama:
```
ollama run hf.co/cstr/multilingual-e5-large-GGUF:IQ4_XS
```

Unsloth Studio

How to use cstr/multilingual-e5-large-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for cstr/multilingual-e5-large-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for cstr/multilingual-e5-large-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for cstr/multilingual-e5-large-GGUF to start chatting

Docker Model Runner
How to use cstr/multilingual-e5-large-GGUF with Docker Model Runner:
```
docker model run hf.co/cstr/multilingual-e5-large-GGUF:IQ4_XS
```

Lemonade

How to use cstr/multilingual-e5-large-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull cstr/multilingual-e5-large-GGUF:IQ4_XS

Run and chat with the model

lemonade run user.multilingual-e5-large-GGUF-IQ4_XS

List all available models

lemonade list

Atomic Chat

cstr commited on Jul 2

Commit

b2f0d1f

verified ·

1 Parent(s): 927a988

A/B summary (cos vs gold)

Browse files

Files changed (1) hide show

multilingual-e5-large-imatrix-ab.txt +5 -0

multilingual-e5-large-imatrix-ab.txt ADDED Viewed

	@@ -0,0 +1,5 @@

+imatrix A/B — e5-large (cstr/multilingual-e5-large-GGUF), cos vs f16/32 gold, n=5, calib=10
+q8_0    imatrix=0  cos_vs_f16=0.999767    601.3MB  -> (A/B only, not uploaded)
+q4_k    imatrix=0  cos_vs_f16=0.981326    450.3MB  -> (A/B only, not uploaded)
+q4_k    imatrix=1  cos_vs_f16=0.983574    450.3MB  -> multilingual-e5-large-q4_k-imatrix.gguf
+iq4_xs  imatrix=1  cos_vs_f16=0.989585    440.9MB  -> multilingual-e5-large-iq4_xs.gguf