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berlin202
/
Fake_Job_predictor_using_llm

PyTorch
GGUF
qwen2
conversational
Model card Files Files and versions
xet
Community

Instructions to use berlin202/Fake_Job_predictor_using_llm 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 berlin202/Fake_Job_predictor_using_llm 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 berlin202/Fake_Job_predictor_using_llm:Q8_0
    # Run inference directly in the terminal:
    llama cli -hf berlin202/Fake_Job_predictor_using_llm:Q8_0
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf berlin202/Fake_Job_predictor_using_llm:Q8_0
    # Run inference directly in the terminal:
    llama cli -hf berlin202/Fake_Job_predictor_using_llm: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 berlin202/Fake_Job_predictor_using_llm:Q8_0
    # Run inference directly in the terminal:
    ./llama-cli -hf berlin202/Fake_Job_predictor_using_llm: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 berlin202/Fake_Job_predictor_using_llm:Q8_0
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf berlin202/Fake_Job_predictor_using_llm:Q8_0
    Use Docker
    docker model run hf.co/berlin202/Fake_Job_predictor_using_llm:Q8_0
  • LM Studio
  • Jan
  • Ollama

    How to use berlin202/Fake_Job_predictor_using_llm with Ollama:

    ollama run hf.co/berlin202/Fake_Job_predictor_using_llm:Q8_0
  • Unsloth Studio

    How to use berlin202/Fake_Job_predictor_using_llm 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 berlin202/Fake_Job_predictor_using_llm 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 berlin202/Fake_Job_predictor_using_llm to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for berlin202/Fake_Job_predictor_using_llm to start chatting
  • Pi

    How to use berlin202/Fake_Job_predictor_using_llm with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf berlin202/Fake_Job_predictor_using_llm:Q8_0
    Configure the model in Pi
    # Install Pi:
    npm install -g @mariozechner/pi-coding-agent
    # Add to ~/.pi/agent/models.json:
    {
      "providers": {
        "llama-cpp": {
          "baseUrl": "http://localhost:8080/v1",
          "api": "openai-completions",
          "apiKey": "none",
          "models": [
            {
              "id": "berlin202/Fake_Job_predictor_using_llm:Q8_0"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Hermes Agent new

    How to use berlin202/Fake_Job_predictor_using_llm with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf berlin202/Fake_Job_predictor_using_llm: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 berlin202/Fake_Job_predictor_using_llm:Q8_0
    Run Hermes
    hermes
  • Atomic Chat new
  • OpenClaw new

    How to use berlin202/Fake_Job_predictor_using_llm with OpenClaw:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf berlin202/Fake_Job_predictor_using_llm: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 "berlin202/Fake_Job_predictor_using_llm: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"
  • Docker Model Runner

    How to use berlin202/Fake_Job_predictor_using_llm with Docker Model Runner:

    docker model run hf.co/berlin202/Fake_Job_predictor_using_llm:Q8_0
  • Lemonade

    How to use berlin202/Fake_Job_predictor_using_llm with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull berlin202/Fake_Job_predictor_using_llm:Q8_0
    Run and chat with the model
    lemonade run user.Fake_Job_predictor_using_llm-Q8_0
    List all available models
    lemonade list
Fake_Job_predictor_using_llm
1.54 GB
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  • 1 contributor
History: 3 commits
berlin202's picture
berlin202
Update generation_config.json
24f2071 verified over 1 year ago
  • .gitattributes
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  • Modelfile
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  • README.md
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  • added_tokens.json
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  • config.json
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  • generation_config.json
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  • merges.txt
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    988 MB
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  • special_tokens_map.json
    617 Bytes
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  • tokenizer.json
    11.4 MB
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  • tokenizer_config.json
    7.36 kB
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  • unsloth.Q8_0.gguf
    531 MB
    xet
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  • vocab.json
    2.78 MB
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