Feature Extraction
GGUF
sentence-transformers
English
Chinese
qwen3_5
llama-cpp
unsloth
text-embeddings
multimodal-embedding
code-search
flatquant
schurscale
quantized
q4_k_m
q5_k_m
q6_k
q8_0
int4
int8
custom_code
Eval Results (legacy)
Instructions to use ewin-reg/WeMM-Embedding-2B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ewin-reg/WeMM-Embedding-2B-GGUF with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ewin-reg/WeMM-Embedding-2B-GGUF", trust_remote_code=True) 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 ewin-reg/WeMM-Embedding-2B-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 ewin-reg/WeMM-Embedding-2B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf ewin-reg/WeMM-Embedding-2B-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ewin-reg/WeMM-Embedding-2B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf ewin-reg/WeMM-Embedding-2B-GGUF:Q4_K_M
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 ewin-reg/WeMM-Embedding-2B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf ewin-reg/WeMM-Embedding-2B-GGUF:Q4_K_M
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 ewin-reg/WeMM-Embedding-2B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf ewin-reg/WeMM-Embedding-2B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/ewin-reg/WeMM-Embedding-2B-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use ewin-reg/WeMM-Embedding-2B-GGUF with Ollama:
ollama run hf.co/ewin-reg/WeMM-Embedding-2B-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use ewin-reg/WeMM-Embedding-2B-GGUF with Docker Model Runner:
docker model run hf.co/ewin-reg/WeMM-Embedding-2B-GGUF:Q4_K_M
- Lemonade
How to use ewin-reg/WeMM-Embedding-2B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ewin-reg/WeMM-Embedding-2B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.WeMM-Embedding-2B-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Ctrl+K