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renezander030
/
browserground

Image-Text-to-Text
PEFT
Safetensors
MLX
GGUF
English
ui-grounding
screen-grounding
browser-agent
claude-computer-use
codex
browser-use
skyvern
hybrid-ai
compound-ai
specialist-model
lora
ollama
apple-silicon
qwen3-vl
gpt-4v-alternative
cost-effective-ai
conversational
Model card Files Files and versions
xet
Community

Instructions to use renezander030/browserground with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use renezander030/browserground with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-VL-2B-Instruct")
    model = PeftModel.from_pretrained(base_model, "renezander030/browserground")
  • MLX

    How to use renezander030/browserground with MLX:

    # Make sure mlx-vlm is installed
    # pip install --upgrade mlx-vlm
    
    from mlx_vlm import load, generate
    from mlx_vlm.prompt_utils import apply_chat_template
    from mlx_vlm.utils import load_config
    
    # Load the model
    model, processor = load("renezander030/browserground")
    config = load_config("renezander030/browserground")
    
    # Prepare input
    image = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
    prompt = "Describe this image."
    
    # Apply chat template
    formatted_prompt = apply_chat_template(
        processor, config, prompt, num_images=1
    )
    
    # Generate output
    output = generate(model, processor, formatted_prompt, image)
    print(output)
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • LM Studio
  • Pi new

    How to use renezander030/browserground with Pi:

    Start the MLX server
    # Install MLX LM:
    uv tool install mlx-lm
    # Start a local OpenAI-compatible server:
    mlx_lm.server --model "renezander030/browserground"
    Configure the model in Pi
    # Install Pi:
    npm install -g @mariozechner/pi-coding-agent
    # Add to ~/.pi/agent/models.json:
    {
      "providers": {
        "mlx-lm": {
          "baseUrl": "http://localhost:8080/v1",
          "api": "openai-completions",
          "apiKey": "none",
          "models": [
            {
              "id": "renezander030/browserground"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Hermes Agent new

    How to use renezander030/browserground with Hermes Agent:

    Start the MLX server
    # Install MLX LM:
    uv tool install mlx-lm
    # Start a local OpenAI-compatible server:
    mlx_lm.server --model "renezander030/browserground"
    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 renezander030/browserground
    Run Hermes
    hermes
browserground
155 MB
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  • 1 contributor
History: 13 commits
renezander030's picture
renezander030
v0.3.1 docs β€” honest UI-TARS-MLX positioning; recipe + tight-RAM-slot framing
44064d7 verified 1 day ago
  • .gitattributes
    1.57 kB
    v0.1 β€” Tier 1.5 LoRA adapter + model card 3 days ago
  • README.md
    14.5 kB
    v0.3.1 docs β€” honest UI-TARS-MLX positioning; recipe + tight-RAM-slot framing 1 day ago
  • adapter_config.json
    1.1 kB
    v0.2 β€” Tier 2 LoRA r32, 26k mixed-domain examples incl. browser, ScreenSpot-v2 60.0% 1 day ago
  • adapter_model.safetensors
    140 MB
    xet
    v0.2 β€” Tier 2 LoRA r32, 26k mixed-domain examples incl. browser, ScreenSpot-v2 60.0% 1 day ago
  • added_tokens.json
    707 Bytes
    v0.1 β€” Tier 1.5 LoRA adapter + model card 3 days ago
  • chat_template.jinja
    5.29 kB
    v0.1 β€” Tier 1.5 LoRA adapter + model card 3 days ago
  • merges.txt
    1.67 MB
    v0.1 β€” Tier 1.5 LoRA adapter + model card 3 days ago
  • preprocessor_config.json
    782 Bytes
    v0.1 β€” Tier 1.5 LoRA adapter + model card 3 days ago
  • special_tokens_map.json
    613 Bytes
    v0.1 β€” Tier 1.5 LoRA adapter + model card 3 days ago
  • tokenizer.json
    11.4 MB
    xet
    v0.1 β€” Tier 1.5 LoRA adapter + model card 3 days ago
  • tokenizer_config.json
    5.45 kB
    v0.1 β€” Tier 1.5 LoRA adapter + model card 3 days ago
  • video_preprocessor_config.json
    817 Bytes
    v0.1 β€” Tier 1.5 LoRA adapter + model card 3 days ago
  • vocab.json
    2.78 MB
    v0.1 β€” Tier 1.5 LoRA adapter + model card 3 days ago