Libraries sentence-transformers How to use leliuga/all-MiniLM-L12-v2-GGUF with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("leliuga/all-MiniLM-L12-v2-GGUF")
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 How to use leliuga/all-MiniLM-L12-v2-GGUF with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("leliuga/all-MiniLM-L12-v2-GGUF")
model = AutoModel.from_pretrained("leliuga/all-MiniLM-L12-v2-GGUF", device_map="auto") Notebooks Google Colab Kaggle Local Apps Settings llama.cpp How to use leliuga/all-MiniLM-L12-v2-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 leliuga/all-MiniLM-L12-v2-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf leliuga/all-MiniLM-L12-v2-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 leliuga/all-MiniLM-L12-v2-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf leliuga/all-MiniLM-L12-v2-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 leliuga/all-MiniLM-L12-v2-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf leliuga/all-MiniLM-L12-v2-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 leliuga/all-MiniLM-L12-v2-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf leliuga/all-MiniLM-L12-v2-GGUF:Q4_K_M Use Docker docker model run hf.co/leliuga/all-MiniLM-L12-v2-GGUF:Q4_K_M LM Studio Jan Ollama How to use leliuga/all-MiniLM-L12-v2-GGUF with Ollama:
ollama run hf.co/leliuga/all-MiniLM-L12-v2-GGUF:Q4_K_M Unsloth Studio How to use leliuga/all-MiniLM-L12-v2-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 leliuga/all-MiniLM-L12-v2-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 leliuga/all-MiniLM-L12-v2-GGUF to start chatting Using HuggingFace Spaces for Unsloth # No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for leliuga/all-MiniLM-L12-v2-GGUF to start chatting Docker Model Runner How to use leliuga/all-MiniLM-L12-v2-GGUF with Docker Model Runner:
docker model run hf.co/leliuga/all-MiniLM-L12-v2-GGUF:Q4_K_M Lemonade How to use leliuga/all-MiniLM-L12-v2-GGUF with Lemonade:
Pull the model # Download Lemonade from https://lemonade-server.ai/
lemonade pull leliuga/all-MiniLM-L12-v2-GGUF:Q4_K_M Run and chat with the model lemonade run user.all-MiniLM-L12-v2-GGUF-Q4_K_M List all available models lemonade list Atomic Chat 
from sentence_transformers import SentenceTransformer model = SentenceTransformer("leliuga/all-MiniLM-L12-v2-GGUF") 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]