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Download README.md from tanmaypathak4/launchready: direct link, hf CLI and curl.
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https://huggingface.co/spaces/tanmaypathak4/launchready/resolve/main/README.md
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hf download hf://spaces/tanmaypathak4/launchready/README.md
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curl -L -o README.md https://huggingface.co/spaces/tanmaypathak4/launchready/resolve/main/README.md
801 Bytes
| title: LaunchReady | |
| colorFrom: green | |
| colorTo: blue | |
| sdk: gradio | |
| sdk_version: 6.31.0 | |
| python_version: "3.11" | |
| app_file: app.py | |
| license: apache-2.0 | |
| short_description: Will this open model fit in your NVIDIA GPU's memory? | |
| # LaunchReady | |
| **Will this open model run on my NVIDIA GPU?** | |
| Think of the model as a stack of papers and your GPU's memory as a desk. LaunchReady works out whether the stack fits on the desk, with room left for everyone using it, before you download it. | |
| Enter a Hugging Face model, a GPU, a context length and a number of users, and get a plain-English answer about memory. Results are projected, not measured, and cover memory only, not speed. No model weights are downloaded. | |
| Source: [github.com/Tanmaypathak18/launchready](https://github.com/Tanmaypathak18/launchready) | |