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lemonilia
/
Limamono-Mistral-7B-v0.50

Text Generation
Transformers
GGUF
English
mistral
Not-For-All-Audiences
8-bit precision
bitsandbytes
Model card Files Files and versions
xet
Community
5

Instructions to use lemonilia/Limamono-Mistral-7B-v0.50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use lemonilia/Limamono-Mistral-7B-v0.50 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="lemonilia/Limamono-Mistral-7B-v0.50")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("lemonilia/Limamono-Mistral-7B-v0.50")
    model = AutoModelForCausalLM.from_pretrained("lemonilia/Limamono-Mistral-7B-v0.50", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use lemonilia/Limamono-Mistral-7B-v0.50 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 lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
    # Run inference directly in the terminal:
    llama cli -hf lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
    # Run inference directly in the terminal:
    llama cli -hf lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
    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 lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
    # Run inference directly in the terminal:
    ./llama-cli -hf lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
    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 lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
    Use Docker
    docker model run hf.co/lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
  • LM Studio
  • Jan
  • vLLM

    How to use lemonilia/Limamono-Mistral-7B-v0.50 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "lemonilia/Limamono-Mistral-7B-v0.50"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "lemonilia/Limamono-Mistral-7B-v0.50",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
  • SGLang

    How to use lemonilia/Limamono-Mistral-7B-v0.50 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 "lemonilia/Limamono-Mistral-7B-v0.50" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "lemonilia/Limamono-Mistral-7B-v0.50",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    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 "lemonilia/Limamono-Mistral-7B-v0.50" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "lemonilia/Limamono-Mistral-7B-v0.50",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Ollama

    How to use lemonilia/Limamono-Mistral-7B-v0.50 with Ollama:

    ollama run hf.co/lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
  • Unsloth Desktop
  • Docker Model Runner

    How to use lemonilia/Limamono-Mistral-7B-v0.50 with Docker Model Runner:

    docker model run hf.co/lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
  • Lemonade

    How to use lemonilia/Limamono-Mistral-7B-v0.50 with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull lemonilia/Limamono-Mistral-7B-v0.50:Q2_K
    Run and chat with the model
    lemonade run user.Limamono-Mistral-7B-v0.50-Q2_K
    List all available models
    lemonade list
  • Atomic Chat
Limamono-Mistral-7B-v0.50
14.2 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 39 commits
lemonilia's picture
lemonilia
Update README.md
1afa249 over 2 years ago
  • SillyTavern Settings
    Upload 2 files almost 3 years ago
  • .gitattributes
    2.1 kB
    v0.50 almost 3 years ago
  • Charlotte.png
    265 kB
    Upload Charlotte.png almost 3 years ago
  • Limamono-Mistral-7B-v0.50-Q2_K.gguf
    3.08 GB
    xet
    v0.50 almost 3 years ago
  • Limamono-Mistral-7B-v0.50-Q5_K_M.gguf
    5.13 GB
    xet
    v0.50 almost 3 years ago
  • Limamono-Mistral-7B-v0.50-Q6_K.gguf
    5.94 GB
    xet
    v0.50 almost 3 years ago
  • README.md
    7.55 kB
    Update README.md over 2 years ago
  • adapter_config.json
    583 Bytes
    Upload 3 files almost 3 years ago
  • adapter_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    84 MB
    xet
    Upload 3 files almost 3 years ago
  • config.json
    1.05 kB
    Upload 3 files almost 3 years ago