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Soulfate24
/
ReaderLM-v2-Paretrix

Text Generation
Transformers
GGUF
multilingual
llama.cpp
quantization
imatrix
hybrid-quantization
pareto
rco
conversational
Model card Files Files and versions
xet
Community

Instructions to use Soulfate24/ReaderLM-v2-Paretrix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Soulfate24/ReaderLM-v2-Paretrix with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="Soulfate24/ReaderLM-v2-Paretrix")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Soulfate24/ReaderLM-v2-Paretrix", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use Soulfate24/ReaderLM-v2-Paretrix 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 Soulfate24/ReaderLM-v2-Paretrix
    # Run inference directly in the terminal:
    llama cli -hf Soulfate24/ReaderLM-v2-Paretrix
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf Soulfate24/ReaderLM-v2-Paretrix
    # Run inference directly in the terminal:
    llama cli -hf Soulfate24/ReaderLM-v2-Paretrix
    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 Soulfate24/ReaderLM-v2-Paretrix
    # Run inference directly in the terminal:
    ./llama-cli -hf Soulfate24/ReaderLM-v2-Paretrix
    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 Soulfate24/ReaderLM-v2-Paretrix
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf Soulfate24/ReaderLM-v2-Paretrix
    Use Docker
    docker model run hf.co/Soulfate24/ReaderLM-v2-Paretrix
  • LM Studio
  • Jan
  • vLLM

    How to use Soulfate24/ReaderLM-v2-Paretrix with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Soulfate24/ReaderLM-v2-Paretrix"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Soulfate24/ReaderLM-v2-Paretrix",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/Soulfate24/ReaderLM-v2-Paretrix
  • SGLang

    How to use Soulfate24/ReaderLM-v2-Paretrix with SGLang:

    Install from pip and serve model
    # Install SGLang from pip:
    pip install sglang
    # Start the SGLang server:
    python3 -m sglang.launch_server \
        --model-path "Soulfate24/ReaderLM-v2-Paretrix" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Soulfate24/ReaderLM-v2-Paretrix",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker images
    docker run --gpus all \
        --shm-size 32g \
        -p 30000:30000 \
        -v ~/.cache/huggingface:/root/.cache/huggingface \
        --env "HF_TOKEN=<secret>" \
        --ipc=host \
        lmsysorg/sglang:latest \
        python3 -m sglang.launch_server \
            --model-path "Soulfate24/ReaderLM-v2-Paretrix" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Soulfate24/ReaderLM-v2-Paretrix",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Ollama

    How to use Soulfate24/ReaderLM-v2-Paretrix with Ollama:

    ollama run hf.co/Soulfate24/ReaderLM-v2-Paretrix
  • Unsloth Desktop
  • Docker Model Runner

    How to use Soulfate24/ReaderLM-v2-Paretrix with Docker Model Runner:

    docker model run hf.co/Soulfate24/ReaderLM-v2-Paretrix
  • Lemonade

    How to use Soulfate24/ReaderLM-v2-Paretrix with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull Soulfate24/ReaderLM-v2-Paretrix
    Run and chat with the model
    lemonade run user.ReaderLM-v2-Paretrix-{{QUANT_TAG}}
    List all available models
    lemonade list
  • Atomic Chat
ReaderLM-v2-Paretrix
6.69 GB
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  • 1 contributor
History: 3 commits
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Soulfate24
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