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landtml
/
d1-2B-RAG-Verifier

Text Classification
Transformers
Safetensors
GGUF
English
lfm3_vl
feature-extraction
rag
hallucination-detection
groundedness
faithfulness
ragtruth
verifier
lora
d1
lfm3
decision-model
custom_code
Eval Results (legacy)
conversational
Model card Files Files and versions
xet
Community

Instructions to use landtml/d1-2B-RAG-Verifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use landtml/d1-2B-RAG-Verifier with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="landtml/d1-2B-RAG-Verifier", trust_remote_code=True)
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoProcessor, AutoModel
    
    processor = AutoProcessor.from_pretrained("landtml/d1-2B-RAG-Verifier", trust_remote_code=True)
    model = AutoModel.from_pretrained("landtml/d1-2B-RAG-Verifier", trust_remote_code=True, device_map="auto")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    inputs = processor.apply_chat_template(
    	messages,
    	add_generation_prompt=True,
    	tokenize=True,
    	return_dict=True,
    	return_tensors="pt",
    ).to(model.device)
    
    outputs = model.generate(**inputs, max_new_tokens=256)
    print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use landtml/d1-2B-RAG-Verifier 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 landtml/d1-2B-RAG-Verifier:Q8_0
    # Run inference directly in the terminal:
    llama cli -hf landtml/d1-2B-RAG-Verifier:Q8_0
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf landtml/d1-2B-RAG-Verifier:Q8_0
    # Run inference directly in the terminal:
    llama cli -hf landtml/d1-2B-RAG-Verifier:Q8_0
    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 landtml/d1-2B-RAG-Verifier:Q8_0
    # Run inference directly in the terminal:
    ./build/bin/llama cli -hf landtml/d1-2B-RAG-Verifier:Q8_0
    Use Docker
    docker model run hf.co/landtml/d1-2B-RAG-Verifier:Q8_0
  • Llama new
  • LM Studio
  • Jan
  • Ollama

    How to use landtml/d1-2B-RAG-Verifier with Ollama:

    ollama run hf.co/landtml/d1-2B-RAG-Verifier:Q8_0
  • Unsloth Desktop
  • Pi

    How to use landtml/d1-2B-RAG-Verifier with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf landtml/d1-2B-RAG-Verifier: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": "landtml/d1-2B-RAG-Verifier:Q8_0"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Docker Model Runner

    How to use landtml/d1-2B-RAG-Verifier with Docker Model Runner:

    docker model run hf.co/landtml/d1-2B-RAG-Verifier:Q8_0
  • Lemonade

    How to use landtml/d1-2B-RAG-Verifier with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull landtml/d1-2B-RAG-Verifier:Q8_0
    Run and chat with the model
    lemonade run user.d1-2B-RAG-Verifier-Q8_0
    List all available models
    lemonade list
  • Hermes Agent

    How to use landtml/d1-2B-RAG-Verifier with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf landtml/d1-2B-RAG-Verifier: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 landtml/d1-2B-RAG-Verifier:Q8_0
    Run Hermes
    hermes
  • Atomic Chat
  • OpenClaw

    How to use landtml/d1-2B-RAG-Verifier with OpenClaw:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf landtml/d1-2B-RAG-Verifier: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 "landtml/d1-2B-RAG-Verifier: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"
d1-2B-RAG-Verifier / eval
535 kB
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  • 1 contributor
History: 1 commit
landtml's picture
landtml
Release d1-2B RAG Verifier
8d9bafb 3 days ago
  • dev_predictions.jsonl
    154 kB
    Release d1-2B RAG Verifier 3 days ago
  • evaluate.py
    2.13 kB
    Release d1-2B RAG Verifier 3 days ago
  • test_predictions.jsonl
    190 kB
    Release d1-2B RAG Verifier 3 days ago
  • test_predictions_untrained.jsonl
    190 kB
    Release d1-2B RAG Verifier 3 days ago