Text Classification
Transformers
GGUF
Transformers.js
multilingual
reranker
cross-encoder
feature-extraction
Instructions to use gpustack/jina-reranker-v2-base-multilingual-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gpustack/jina-reranker-v2-base-multilingual-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gpustack/jina-reranker-v2-base-multilingual-GGUF")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("gpustack/jina-reranker-v2-base-multilingual-GGUF", device_map="auto") - Transformers.js
How to use gpustack/jina-reranker-v2-base-multilingual-GGUF with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'gpustack/jina-reranker-v2-base-multilingual-GGUF'); - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use gpustack/jina-reranker-v2-base-multilingual-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 gpustack/jina-reranker-v2-base-multilingual-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf gpustack/jina-reranker-v2-base-multilingual-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 gpustack/jina-reranker-v2-base-multilingual-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf gpustack/jina-reranker-v2-base-multilingual-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 gpustack/jina-reranker-v2-base-multilingual-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf gpustack/jina-reranker-v2-base-multilingual-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 gpustack/jina-reranker-v2-base-multilingual-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf gpustack/jina-reranker-v2-base-multilingual-GGUF:Q4_K_M
Use Docker
docker model run hf.co/gpustack/jina-reranker-v2-base-multilingual-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use gpustack/jina-reranker-v2-base-multilingual-GGUF with Ollama:
ollama run hf.co/gpustack/jina-reranker-v2-base-multilingual-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use gpustack/jina-reranker-v2-base-multilingual-GGUF with Docker Model Runner:
docker model run hf.co/gpustack/jina-reranker-v2-base-multilingual-GGUF:Q4_K_M
- Lemonade
How to use gpustack/jina-reranker-v2-base-multilingual-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull gpustack/jina-reranker-v2-base-multilingual-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.jina-reranker-v2-base-multilingual-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Ctrl+K