pytorch_influence_functions: Improve Model Transparency
Pytorch_influence_functions helps startup founders understand and analyze the predictions made by their deep learning models by identifying the most influential training data points
- •When you need to debug and understand why your model is making certain predictions
- •When you want to identify biases in your training data and their impact on model predictions
- •When you need to explain model decisions to stakeholders or customers
python examples/influence_functions_example.py --dataset cifar10 --model resnet18 --num_samples 100
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/pytorch-influence-functions && curl -fsSL https://workflowstacks.com/api/skills/pytorch-influence-functions/claude-skill -o ~/.claude/skills/pytorch-influence-functions/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/pytorch-influence-functions && curl -fsSL https://workflowstacks.com/api/skills/pytorch-influence-functions/claude-skill -o ~/.claude/skills/pytorch-influence-functions/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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