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nesall
/
bge-code-v1-Q8_0-GGUF

Sentence Similarity
sentence-transformers
GGUF
Transformers
Chinese
English
feature-extraction
llama-cpp
gguf-my-repo
conversational
Model card Files Files and versions
xet
Community

Instructions to use nesall/bge-code-v1-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use nesall/bge-code-v1-Q8_0-GGUF with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("nesall/bge-code-v1-Q8_0-GGUF")
    
    sentences = [
        "那是 個快樂的人",
        "那是 條快樂的狗",
        "那是 個非常幸福的人",
        "今天是晴天"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Transformers

    How to use nesall/bge-code-v1-Q8_0-GGUF with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("nesall/bge-code-v1-Q8_0-GGUF", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use nesall/bge-code-v1-Q8_0-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 nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    # Run inference directly in the terminal:
    llama cli -hf nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    # Run inference directly in the terminal:
    llama cli -hf nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    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 nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    # Run inference directly in the terminal:
    ./llama-cli -hf nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    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 nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    Use Docker
    docker model run hf.co/nesall/bge-code-v1-Q8_0-GGUF:Q8_0
  • LM Studio
  • Jan
  • Ollama

    How to use nesall/bge-code-v1-Q8_0-GGUF with Ollama:

    ollama run hf.co/nesall/bge-code-v1-Q8_0-GGUF:Q8_0
  • Unsloth Desktop
  • Pi

    How to use nesall/bge-code-v1-Q8_0-GGUF with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    Configure the model in Pi
    # Install Pi:
    npm install -g @earendil-works/pi-coding-agent
    # Add to ~/.pi/agent/models.json:
    {
      "providers": {
        "llama-cpp": {
          "baseUrl": "http://localhost:8080/v1",
          "api": "openai-completions",
          "apiKey": "none",
          "models": [
            {
              "id": "nesall/bge-code-v1-Q8_0-GGUF:Q8_0"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Docker Model Runner

    How to use nesall/bge-code-v1-Q8_0-GGUF with Docker Model Runner:

    docker model run hf.co/nesall/bge-code-v1-Q8_0-GGUF:Q8_0
  • Lemonade

    How to use nesall/bge-code-v1-Q8_0-GGUF with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    Run and chat with the model
    lemonade run user.bge-code-v1-Q8_0-GGUF-Q8_0
    List all available models
    lemonade list
  • Hermes Agent

    How to use nesall/bge-code-v1-Q8_0-GGUF with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    Configure Hermes
    # Install Hermes:
    curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
    hermes setup
    # Point Hermes at the local server:
    hermes config set model.provider custom
    hermes config set model.base_url http://127.0.0.1:8080/v1
    hermes config set model.default nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    Run Hermes
    hermes
  • Atomic Chat
  • OpenClaw

    How to use nesall/bge-code-v1-Q8_0-GGUF with OpenClaw:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf nesall/bge-code-v1-Q8_0-GGUF:Q8_0
    Configure OpenClaw
    # Install OpenClaw:
    npm install -g openclaw@latest
    # Register the local server and set it as the default model:
    openclaw onboard --non-interactive --mode local \
      --auth-choice custom-api-key \
      --custom-base-url http://127.0.0.1:8080/v1 \
      --custom-model-id "nesall/bge-code-v1-Q8_0-GGUF:Q8_0" \
      --custom-provider-id llama-cpp \
      --custom-compatibility openai \
      --custom-text-input \
      --accept-risk \
      --skip-health
    Run OpenClaw
    openclaw agent --local --agent main --message "Hello from Hugging Face"
bge-code-v1-Q8_0-GGUF
1.65 GB
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  • 1 contributor
History: 3 commits
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nesall
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  • .gitattributes
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    Upload bge-code-v1-q8_0.gguf with huggingface_hub 10 months ago
  • README.md
    1.81 kB
    Upload README.md with huggingface_hub 10 months ago
  • bge-code-v1-q8_0.gguf
    1.65 GB
    xet
    Upload bge-code-v1-q8_0.gguf with huggingface_hub 10 months ago