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Published on 2/26/2025
PyTorch Assistant

Rules
Prompts
Models
Context
anthropic Claude 3.7 Sonnet model icon

Claude 3.7 Sonnet

anthropic

200kinput·8.192koutput
mistral Codestral model icon

Codestral

mistral

voyage voyage-code-3 model icon

voyage-code-3

voyage

voyage Voyage AI rerank-2 model icon

Voyage AI rerank-2

voyage

- You are a PyTorch ML engineer
- Use type hints consistently
- Optimize for readability over premature optimization
- Write modular code, using separate files for models, data loading, training, and evaluation
- Follow PEP8 style guide for Python code
PyTorchhttps://pytorch.org/docs/stable/index.html
torch.nn Docshttps://pytorch.org/docs/stable/nn.html

Prompts

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Equations
Convert module to equations
Please convert this PyTorch module to equations. Use KaTex, surrounding any equations in double dollar signs, like $$E_1 = E_2$$. Your output should include step by step explanations of what happens at each step and a very short explanation of the purpose of that step.
Training Loop
Create a training loop
Please create a training loop following these guidelines:
- Include validation step
- Add proper device handling (CPU/GPU)
- Implement gradient clipping
- Add learning rate scheduling
- Include early stopping
- Add progress bars using tqdm
- Implement checkpointing
New Module
Create a new PyTorch module
Please create a new PyTorch module following these guidelines:
- Include docstrings for the model class and methods
- Add type hints for all parameters
- Add basic validation in __init__

Context

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@diff
Reference all of the changes you've made to your current branch
@codebase
Reference the most relevant snippets from your codebase
@url
Reference the markdown converted contents of a given URL
@folder
Uses the same retrieval mechanism as @Codebase, but only on a single folder
@terminal
Reference the last command you ran in your IDE's terminal and its output
@code
Reference specific functions or classes from throughout your project
@file
Reference any file in your current workspace

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