Libraries sentence-transformers How to use second-state/jina-embeddings-v2-base-code-GGUF with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("second-state/jina-embeddings-v2-base-code-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] Transformers How to use second-state/jina-embeddings-v2-base-code-GGUF with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("feature-extraction", model="second-state/jina-embeddings-v2-base-code-GGUF", trust_remote_code=True) # Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("second-state/jina-embeddings-v2-base-code-GGUF", trust_remote_code=True)
model = AutoModelForMaskedLM.from_pretrained("second-state/jina-embeddings-v2-base-code-GGUF", trust_remote_code=True) Transformers.js How to use second-state/jina-embeddings-v2-base-code-GGUF with Transformers.js:
// npm i @huggingface/transformers
import { pipeline } from '@huggingface/transformers';
// Allocate pipeline
const pipe = await pipeline('feature-extraction', 'second-state/jina-embeddings-v2-base-code-GGUF'); llama-cpp-python How to use second-state/jina-embeddings-v2-base-code-GGUF with llama-cpp-python:
# !pip install llama-cpp-python
from llama_cpp import Llama
llm = Llama.from_pretrained(
repo_id="second-state/jina-embeddings-v2-base-code-GGUF",
filename="jina-embeddings-v2-base-code-Q2_K.gguf",
)
output = llm(
"Once upon a time,",
max_tokens=512,
echo=True
)
print(output) Notebooks Google Colab Kaggle Local Apps llama.cpp How to use second-state/jina-embeddings-v2-base-code-GGUF with llama.cpp:
Install from brew brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf second-state/jina-embeddings-v2-base-code-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf second-state/jina-embeddings-v2-base-code-GGUF:Q4_K_M Install from WinGet (Windows) winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf second-state/jina-embeddings-v2-base-code-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf second-state/jina-embeddings-v2-base-code-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/jina-embeddings-v2-base-code-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf second-state/jina-embeddings-v2-base-code-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/jina-embeddings-v2-base-code-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf second-state/jina-embeddings-v2-base-code-GGUF:Q4_K_M Use Docker docker model run hf.co/second-state/jina-embeddings-v2-base-code-GGUF:Q4_K_M LM Studio Jan Ollama How to use second-state/jina-embeddings-v2-base-code-GGUF with Ollama:
ollama run hf.co/second-state/jina-embeddings-v2-base-code-GGUF:Q4_K_M Unsloth Studio new How to use second-state/jina-embeddings-v2-base-code-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/jina-embeddings-v2-base-code-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/jina-embeddings-v2-base-code-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/jina-embeddings-v2-base-code-GGUF to start chatting Docker Model Runner How to use second-state/jina-embeddings-v2-base-code-GGUF with Docker Model Runner:
docker model run hf.co/second-state/jina-embeddings-v2-base-code-GGUF:Q4_K_M Lemonade How to use second-state/jina-embeddings-v2-base-code-GGUF with Lemonade:
Pull the model # Download Lemonade from https://lemonade-server.ai/
lemonade pull second-state/jina-embeddings-v2-base-code-GGUF:Q4_K_M Run and chat with the model lemonade run user.jina-embeddings-v2-base-code-GGUF-Q4_K_M List all available models lemonade list 
