Feature Extraction
GGUF
sentence-transformers
llama.cpp
embedding
multimodal
multilingual
quantized
imatrix
Instructions to use ngquocvinh/EmbeddingGemma-2-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ngquocvinh/EmbeddingGemma-2-GGUF with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ngquocvinh/EmbeddingGemma-2-GGUF") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ngquocvinh/EmbeddingGemma-2-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible embeddings server: llama serve -hf ngquocvinh/EmbeddingGemma-2-GGUF:Q4_K_M --embeddings
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible embeddings server: llama serve -hf ngquocvinh/EmbeddingGemma-2-GGUF:Q4_K_M --embeddings
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible embeddings server: ./llama-server -hf ngquocvinh/EmbeddingGemma-2-GGUF:Q4_K_M --embeddings
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 embeddings server: ./build/bin/llama-server -hf ngquocvinh/EmbeddingGemma-2-GGUF:Q4_K_M --embeddings
- LM Studio
- Jan
- Ollama
How to use ngquocvinh/EmbeddingGemma-2-GGUF with Ollama:
ollama run hf.co/ngquocvinh/EmbeddingGemma-2-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use ngquocvinh/EmbeddingGemma-2-GGUF with Docker Model Runner:
docker model run hf.co/ngquocvinh/EmbeddingGemma-2-GGUF:Q4_K_M
- Lemonade
How to use ngquocvinh/EmbeddingGemma-2-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ngquocvinh/EmbeddingGemma-2-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.EmbeddingGemma-2-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download reproducibility/embedding-evaluation.tsv from ngquocvinh/EmbeddingGemma-2-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 2.63 kB
-
https://huggingface.co/ngquocvinh/EmbeddingGemma-2-GGUF/resolve/main/reproducibility/embedding-evaluation.tsv
- Command line
-
hf download hf://ngquocvinh/EmbeddingGemma-2-GGUF/reproducibility/embedding-evaluation.tsv
-
curl -L -o embedding-evaluation.tsv https://huggingface.co/ngquocvinh/EmbeddingGemma-2-GGUF/resolve/main/reproducibility/embedding-evaluation.tsv
2.63 kB
| file size_gb pairs spearman_human pearson_human mean_embedding_cosine_vs_bf16 p05_embedding_cosine_vs_bf16 status | |
| BF16 reference 0.557950 1379 0.875414 0.865994 1.000000 1.000000 REFERENCE | |
| EmbeddingGemma-2-Q8_0.gguf 0.309856 1379 0.875125 0.865776 0.999930 0.999903 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-Q6_K.gguf 0.245765 1379 0.874311 0.864975 0.999548 0.999373 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-Q5_K_M.gguf 0.212759 1379 0.874081 0.864863 0.999190 0.998841 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-Q5_K_S.gguf 0.210670 1379 0.874892 0.865614 0.999104 0.998727 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-Q4_K_M.gguf 0.181695 1379 0.872686 0.864659 0.997824 0.996776 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-Q4_K_S.gguf 0.178164 1379 0.873112 0.864908 0.997379 0.996201 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-IQ4_NL.gguf 0.177640 1379 0.871242 0.862865 0.996884 0.995270 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-IQ4_XS.gguf 0.169383 1379 0.871200 0.863202 0.996687 0.994900 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-Q3_K_L.gguf 0.154440 1379 0.869874 0.860846 0.993184 0.989422 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-Q3_K_M.gguf 0.148870 1379 0.869604 0.860705 0.992364 0.988323 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-IQ3_M.gguf 0.145749 1379 0.870880 0.862364 0.992638 0.988771 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-Q3_K_S.gguf 0.142546 1379 0.866108 0.853203 0.987335 0.981859 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-IQ3_S.gguf 0.142546 1379 0.870980 0.863233 0.990906 0.986058 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-IQ3_XS.gguf 0.139793 1379 0.867124 0.859804 0.989128 0.983518 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-IQ3_XXS.gguf 0.135776 1379 0.862974 0.858534 0.983963 0.976505 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-IQ2_M.gguf 0.130910 1379 0.862532 0.861373 0.971570 0.960803 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-IQ2_S.gguf 0.127600 1379 0.856632 0.851405 0.963077 0.949864 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-Q2_K.gguf 0.120394 1379 0.856144 0.854341 0.972891 0.960440 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-Q2_K_S.gguf 0.116446 1379 0.843346 0.843931 0.962411 0.948042 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-IQ2_XS.gguf 0.110946 1379 0.846829 0.838447 0.944608 0.927359 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-IQ2_XXS.gguf 0.107178 1379 0.834294 0.827123 0.919032 0.899266 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-IQ1_M.gguf 0.103041 1379 0.797642 0.801111 0.819494 0.778721 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-IQ1_S.gguf 0.100558 1379 0.761951 0.772373 0.768243 0.728349 EVALUATED_VALID_OUTPUT | |
| EmbeddingGemma-2-Q1_0.gguf 0.066163 1379 0.061457 0.062574 0.513763 0.425907 EVALUATED_VALID_OUTPUT | |