Instructions to use second-state/All-MiniLM-L6-v2-Embedding-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use second-state/All-MiniLM-L6-v2-Embedding-GGUF with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("second-state/All-MiniLM-L6-v2-Embedding-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] - Transformers
How to use second-state/All-MiniLM-L6-v2-Embedding-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="second-state/All-MiniLM-L6-v2-Embedding-GGUF")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("second-state/All-MiniLM-L6-v2-Embedding-GGUF") model = AutoModel.from_pretrained("second-state/All-MiniLM-L6-v2-Embedding-GGUF") - llama-cpp-python
How to use second-state/All-MiniLM-L6-v2-Embedding-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="second-state/All-MiniLM-L6-v2-Embedding-GGUF", filename="all-MiniLM-L6-v2-Q2_K.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use second-state/All-MiniLM-L6-v2-Embedding-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 second-state/All-MiniLM-L6-v2-Embedding-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf second-state/All-MiniLM-L6-v2-Embedding-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 second-state/All-MiniLM-L6-v2-Embedding-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf second-state/All-MiniLM-L6-v2-Embedding-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 second-state/All-MiniLM-L6-v2-Embedding-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf second-state/All-MiniLM-L6-v2-Embedding-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 second-state/All-MiniLM-L6-v2-Embedding-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf second-state/All-MiniLM-L6-v2-Embedding-GGUF:Q4_K_M
Use Docker
docker model run hf.co/second-state/All-MiniLM-L6-v2-Embedding-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use second-state/All-MiniLM-L6-v2-Embedding-GGUF with Ollama:
ollama run hf.co/second-state/All-MiniLM-L6-v2-Embedding-GGUF:Q4_K_M
- Unsloth Studio
How to use second-state/All-MiniLM-L6-v2-Embedding-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 second-state/All-MiniLM-L6-v2-Embedding-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 second-state/All-MiniLM-L6-v2-Embedding-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for second-state/All-MiniLM-L6-v2-Embedding-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use second-state/All-MiniLM-L6-v2-Embedding-GGUF with Docker Model Runner:
docker model run hf.co/second-state/All-MiniLM-L6-v2-Embedding-GGUF:Q4_K_M
- Lemonade
How to use second-state/All-MiniLM-L6-v2-Embedding-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull second-state/All-MiniLM-L6-v2-Embedding-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.All-MiniLM-L6-v2-Embedding-GGUF-Q4_K_M
List all available models
lemonade list
Commit History
Update README.md b2a6536 verified
Upload config.json 4505133 verified
Update README.md 8cb18b1 verified
Update README.md 1146e4d verified
Update README.md c92486c verified
Update 75a3535
Xin Liu commited on
Add models e2cd77b
Xin Liu commited on
Update 6587ec7
Xin Liu commited on
Add Q8_0 model aa38cf2
Xin Liu commited on
Add f16 model 0a7803f
Xin Liu commited on
Add Q5_K_M model 919ed6b
Xin Liu commited on