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Phora68
/
rapha

Safetensors
GGUF
English
qwen2
clinical
medical
healthcare
qlora
unsloth
chatml
rapha
8-bit precision
conversational
Model card Files Files and versions
xet
Community

Instructions to use Phora68/rapha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use Phora68/rapha 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 Phora68/rapha:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf Phora68/rapha:Q4_K_M
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf Phora68/rapha:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf Phora68/rapha: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 Phora68/rapha:Q4_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf Phora68/rapha: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 Phora68/rapha:Q4_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf Phora68/rapha:Q4_K_M
    Use Docker
    docker model run hf.co/Phora68/rapha:Q4_K_M
  • LM Studio
  • Jan
  • Ollama

    How to use Phora68/rapha with Ollama:

    ollama run hf.co/Phora68/rapha:Q4_K_M
  • Unsloth Studio

    How to use Phora68/rapha 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 Phora68/rapha 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 Phora68/rapha to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for Phora68/rapha to start chatting
  • Atomic Chat new
  • Docker Model Runner

    How to use Phora68/rapha with Docker Model Runner:

    docker model run hf.co/Phora68/rapha:Q4_K_M
  • Lemonade

    How to use Phora68/rapha with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull Phora68/rapha:Q4_K_M
    Run and chat with the model
    lemonade run user.rapha-Q4_K_M
    List all available models
    lemonade list
rapha
33.3 GB
Ctrl+K
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  • 1 contributor
History: 31 commits
Phora68's picture
Phora68
Add Qwen2.5-3B-Instruct.Q8_0.gguf
b6ce3dd verified about 2 hours ago
  • datasets
    Add dataset: preference_pairs.jsonl 8 days ago
  • gguf
    Add Qwen2.5-3B-Instruct.Q8_0.gguf about 2 hours ago
  • merged
    Add merged fp16 model about 3 hours ago
  • .gitattributes
    2.44 kB
    Add Qwen2.5-3B-Instruct.Q8_0.gguf about 2 hours ago
  • Modelfile.q4_k_m
    925 Bytes
    Add Ollama Modelfile 8 days ago
  • README.md
    3.11 kB
    Update model card about 3 hours ago
  • adapter_config.json
    1.25 kB
    Upload model trained with Unsloth about 3 hours ago
  • adapter_model.safetensors
    479 MB
    xet
    Upload model trained with Unsloth about 3 hours ago
  • chat_template.jinja
    398 Bytes
    Upload model trained with Unsloth 8 days ago
  • config.json
    1.79 kB
    Trained with Unsloth - config 8 days ago
  • generation_config.json
    239 Bytes
    Upload model trained with Unsloth 8 days ago
  • merged.Q4_K_M.gguf
    1.93 GB
    xet
    Trained with Unsloth 8 days ago
  • model.safetensors
    2.05 GB
    xet
    Upload model trained with Unsloth 8 days ago
  • rapha-q4_k_m.gguf
    7.48 GB
    xet
    Add rapha-q4_k_m.gguf (Q4_K_M quantisation) 3 months ago
  • tokenizer.json
    11.4 MB
    xet
    Upload model trained with Unsloth 8 days ago
  • tokenizer_config.json
    4.26 kB
    Upload model trained with Unsloth about 3 hours ago