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Check if a HuggingFace model will run on your GPU.

fitgpu takes a HuggingFace model ID and tells you whether the model's weights will fit in your GPU's available VRAM.

How?

  1. Gets model's file metadata from HuggingFace (weights are not downloaded)
  2. Sums up the sizes of all weight files (.safetensors / .bin)
  3. Queries your GPU's free VRAM using the NVIDIA driver
  4. Compares and shows the result

Installation

pip install fitgpu

Use

fitgpu <model_id> [--token TOKEN]
  • model_id — HuggingFace model ID (e.g. google/gemma-2-2b)
  • --token TOKEN — optional, HuggingFace API token for gated/private models

Public models

fitgpu google/gemma-2-2b

Gated models

fitgpu meta-llama/Llama-2-7b-hf --token hf_YOUR_TOKEN

Example

$ fitgpu google/gemma-2-2b
model : google/gemma-2-2b
size  : 4.89 GB (weights on disk)

GPU 0: NVIDIA RTX 4090
  VRAM : 24.00 GB total, 22.31 GB free
  result: fits

Metadata

Release files for fitgpu 0.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for fitgpu 0.1.1
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fitgpu-0.1.1.tar.gz 2.8 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for fitgpu 0.1.1
File Interpreter ABI Platform
fitgpu-0.1.1-py3-none-any.whl Python 3 none any Details

Total release size: 6.4 kB

Release files / fitgpu-0.1.1.tar.gz

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