Instructions to use anerjy/step37-mlx-vlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use anerjy/step37-mlx-vlm 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("anerjy/step37-mlx-vlm") config = load_config("anerjy/step37-mlx-vlm") # 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 Settings
- LM Studio
anerjy commited on
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Parent(s): e5c7c6c
Untrack CLAUDE.md (privacy: contains internal infra refs)
Browse filesCLAUDE.md is local-only — it accumulates API keys, internal IPs,
engine home/ + scripts dir paths, com.user.* launchd labels, and other
private infrastructure detail that should not appear in any public
remote (GitHub or HF).
git rm --cached only — the file stays on disk for Claude Code to read.
Added to .gitignore so future edits don't accidentally re-stage it.
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# Local-only — Claude Code notes with internal infra refs.
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