Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

eyad-silx
/
progress

GGUF
conversational
Model card Files Files and versions
xet
Community

Instructions to use eyad-silx/progress 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 eyad-silx/progress 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 eyad-silx/progress
    # Run inference directly in the terminal:
    llama cli -hf eyad-silx/progress
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf eyad-silx/progress
    # Run inference directly in the terminal:
    llama cli -hf eyad-silx/progress
    Build from source code
    git clone https://github.com/ggml-org/llama.cpp.git
    cd llama.cpp
    cmake -B build
    cmake --build build -j --target llama-app
    # Start a local OpenAI-compatible server with a web UI:
    ./build/bin/llama serve -hf eyad-silx/progress
    # Run inference directly in the terminal:
    ./build/bin/llama cli -hf eyad-silx/progress
    Use Docker
    docker model run hf.co/eyad-silx/progress
  • Llama new
  • LM Studio
  • Jan
  • Ollama

    How to use eyad-silx/progress with Ollama:

    ollama run hf.co/eyad-silx/progress
  • Unsloth Desktop
  • Pi

    How to use eyad-silx/progress with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf eyad-silx/progress
    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": "eyad-silx/progress"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Docker Model Runner

    How to use eyad-silx/progress with Docker Model Runner:

    docker model run hf.co/eyad-silx/progress
  • Lemonade

    How to use eyad-silx/progress with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull eyad-silx/progress
    Run and chat with the model
    lemonade run user.progress-{{QUANT_TAG}}
    List all available models
    lemonade list
  • Hermes Agent

    How to use eyad-silx/progress with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf eyad-silx/progress
    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 eyad-silx/progress
    Run Hermes
    hermes
  • Atomic Chat
  • OpenClaw

    How to use eyad-silx/progress with OpenClaw:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf eyad-silx/progress
    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 "eyad-silx/progress" \
      --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"
progress / artifacts /scripts
54.7 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 20 commits
eyad-silx's picture
eyad-silx
push artifacts/scripts/hf_push.py
8aed8bf verified 13 days ago
  • build_king_hf.py
    2.63 kB
    push artifacts/scripts/build_king_hf.py 14 days ago
  • eval_seq.py
    5.9 kB
    push artifacts/scripts/eval_seq.py 14 days ago
  • gen_teacher.py
    2.37 kB
    push artifacts/scripts/gen_teacher.py 14 days ago
  • hf_push.py
    10.3 kB
    push artifacts/scripts/hf_push.py 13 days ago
  • identity_check.py
    3.55 kB
    push artifacts/scripts/identity_check.py 14 days ago
  • make_traindata.py
    2.23 kB
    push artifacts/scripts/make_traindata.py 14 days ago
  • qat.py
    7.99 kB
    push artifacts/scripts/qat.py 14 days ago
  • qat_norms.py
    4.65 kB
    push artifacts/scripts/qat_norms.py 14 days ago
  • read_identity.py
    595 Bytes
    push artifacts/scripts/read_identity.py 14 days ago
  • run_identity.sh
    368 Bytes
    push artifacts/scripts/run_identity.sh 14 days ago
  • run_m2.sh
    353 Bytes
    push artifacts/scripts/run_m2.sh 14 days ago
  • run_m3.sh
    350 Bytes
    push artifacts/scripts/run_m3.sh 14 days ago
  • run_measure.sh
    356 Bytes
    push artifacts/scripts/run_measure.sh 14 days ago
  • scale_refit.py
    6.23 kB
    push artifacts/scripts/scale_refit.py 14 days ago
  • scale_refit_gpu.py
    4.92 kB
    push artifacts/scripts/scale_refit_gpu.py 14 days ago
  • setup_h100.sh
    1.91 kB
    push artifacts/scripts/setup_h100.sh 14 days ago