Instructions to use Snowflake/snowflake-arctic-embed-m-v1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Snowflake/snowflake-arctic-embed-m-v1.5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Snowflake/snowflake-arctic-embed-m-v1.5") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers.js
How to use Snowflake/snowflake-arctic-embed-m-v1.5 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('sentence-similarity', 'Snowflake/snowflake-arctic-embed-m-v1.5'); - llama-cpp-python
How to use Snowflake/snowflake-arctic-embed-m-v1.5 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Snowflake/snowflake-arctic-embed-m-v1.5", filename="gguf/snowflake-arctic-embed-m-v1.5-bf16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Snowflake/snowflake-arctic-embed-m-v1.5 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 Snowflake/snowflake-arctic-embed-m-v1.5:BF16 # Run inference directly in the terminal: llama cli -hf Snowflake/snowflake-arctic-embed-m-v1.5:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Snowflake/snowflake-arctic-embed-m-v1.5:BF16 # Run inference directly in the terminal: llama cli -hf Snowflake/snowflake-arctic-embed-m-v1.5:BF16
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 Snowflake/snowflake-arctic-embed-m-v1.5:BF16 # Run inference directly in the terminal: ./llama-cli -hf Snowflake/snowflake-arctic-embed-m-v1.5:BF16
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 Snowflake/snowflake-arctic-embed-m-v1.5:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Snowflake/snowflake-arctic-embed-m-v1.5:BF16
Use Docker
docker model run hf.co/Snowflake/snowflake-arctic-embed-m-v1.5:BF16
- LM Studio
- Jan
- Ollama
How to use Snowflake/snowflake-arctic-embed-m-v1.5 with Ollama:
ollama run hf.co/Snowflake/snowflake-arctic-embed-m-v1.5:BF16
- Unsloth Studio
How to use Snowflake/snowflake-arctic-embed-m-v1.5 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 Snowflake/snowflake-arctic-embed-m-v1.5 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 Snowflake/snowflake-arctic-embed-m-v1.5 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Snowflake/snowflake-arctic-embed-m-v1.5 to start chatting
- Atomic Chat new
- Docker Model Runner
How to use Snowflake/snowflake-arctic-embed-m-v1.5 with Docker Model Runner:
docker model run hf.co/Snowflake/snowflake-arctic-embed-m-v1.5:BF16
- Lemonade
How to use Snowflake/snowflake-arctic-embed-m-v1.5 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Snowflake/snowflake-arctic-embed-m-v1.5:BF16
Run and chat with the model
lemonade run user.snowflake-arctic-embed-m-v1.5-BF16
List all available models
lemonade list
Languages?
Can someone share the supported languages for this model?
The model was trained specifically for English language retrieval.
@lukemerrick Are there any plans to bring out a multilingual version? That would be very valuable! If you have recommendations for multilingual alternatives, those are welcome too.
What language(a) are you trying to support, @BramVanroy ? I don't think my team maintains any kind of public roadmap I can share, but we always appreciate user input!
@lukemerrick I'd be really happy to get some more powerful models for Dutch out there. I've been training a lot of generative models, but for retrieving/embedding we could really use new, high quality models such as Snowflake has provided for English!
By the way, the Netherlands Forensic Institute has released some datasets translated to Dutch in case anyone is looking for training data: https://huggingface.co/NetherlandsForensicInstitute
@BramVanroy @Mazyod Come check out our new multilingual models! https://huggingface.co/Snowflake/snowflake-arctic-embed-l-v2.0
This is really cool, we have downloaded it already to benchmark it against other Arabic embedding models. Thanks!!