Instructions to use SciTools/embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use SciTools/embedding 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 SciTools/embedding:F16
# Run inference directly in the terminal:
llama cli -hf SciTools/embedding:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf SciTools/embedding:F16
# Run inference directly in the terminal:
llama cli -hf SciTools/embedding:F16

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 SciTools/embedding:F16
# Run inference directly in the terminal:
./llama-cli -hf SciTools/embedding:F16

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 SciTools/embedding:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SciTools/embedding:F16

Use Docker

docker model run hf.co/SciTools/embedding:F16

LM Studio
Jan
Ollama
How to use SciTools/embedding with Ollama:
```
ollama run hf.co/SciTools/embedding:F16
```

Unsloth Studio

How to use SciTools/embedding 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 SciTools/embedding 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 SciTools/embedding to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for SciTools/embedding to start chatting

Docker Model Runner
How to use SciTools/embedding with Docker Model Runner:
```
docker model run hf.co/SciTools/embedding:F16
```

Lemonade

How to use SciTools/embedding with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SciTools/embedding:F16

Run and chat with the model

lemonade run user.embedding-F16

List all available models

lemonade list

Atomic Chat

zenpeach commited on 4 days ago

Commit

8b5a9c9

verified ·

1 Parent(s): 7fff4e3

Put license front matter at the top so HF registers it

Browse files

Files changed (1) hide show

README.md +4 -4

README.md CHANGED Viewed

@@ -1,3 +1,7 @@
 A small English embedding model by BAAI (Beijing Academy of Artificial Intelligence).
 This repository hosts the versions of the model used by Understand to generate embeddings for semantic search, allowing users to search their codebase by meaning rather than exact keyword matches.
@@ -12,7 +16,3 @@ The GGUF was converted from `BAAI/bge-small-en-v1.5` with llama.cpp's
 (cosine similarity 1.00000). Note the ONNX path used mean pooling while the
 GGUF uses BGE's specified CLS pooling, so indexes built with one are not
 comparable with the other.
----
-license: mit
----

+---
+license: mit
+---
 A small English embedding model by BAAI (Beijing Academy of Artificial Intelligence).
 This repository hosts the versions of the model used by Understand to generate embeddings for semantic search, allowing users to search their codebase by meaning rather than exact keyword matches.
 (cosine similarity 1.00000). Note the ONNX path used mean pooling while the
 GGUF uses BGE's specified CLS pooling, so indexes built with one are not
 comparable with the other.