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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.

  • Libraries
  • llama-cpp-python

    How to use Phora68/rapha with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="Phora68/rapha",
    	filename="gguf/rapha-qwen25-3b-q4_k_m.gguf",
    )
    
    llm.create_chat_completion(
    	messages = "No input example has been defined for this model task."
    )
  • 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 / datasets
256 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 8 commits
Phora68's picture
Phora68
Add dataset: preference_pairs.jsonl
c3b0f72 verified 7 days ago
  • adversarial.jsonl
    9.63 MB
    Add dataset: adversarial.jsonl 7 days ago
  • full_arc_conversations.jsonl
    101 MB
    xet
    Add dataset: full_arc_conversations.jsonl 7 days ago
  • preference_pairs.jsonl
    2.29 MB
    Add dataset: preference_pairs.jsonl 7 days ago
  • stage1_greetings.jsonl
    20 MB
    xet
    Add dataset: stage1_greetings.jsonl 7 days ago
  • stage2_opqrst.jsonl
    48.7 MB
    xet
    Add dataset: stage2_opqrst.jsonl 7 days ago
  • stage3_history.jsonl
    58.1 MB
    xet
    Add dataset: stage3_history.jsonl 7 days ago
  • stage4_red_flags.jsonl
    15.1 MB
    xet
    Add dataset: stage4_red_flags.jsonl 7 days ago
  • val_sharegpt.jsonl
    1.41 MB
    Add dataset: val_sharegpt.jsonl 7 days ago