Inspect Command - Entrenar - Training & Optimization Library
Description: A comprehensive guide to building neural network training systems with autograd, optimizers, LoRA/QLoRA, and quantization using EXTREME TDD methodology

# Inspect Command

The `entrenar inspect` command provides data and model inspection capabilities for SafeTensors, GGUF, Parquet, and CSV files.

## Usage

    entrenar inspect <INPUT> [OPTIONS]

## Arguments

Argument | Description
--- | ---
`<INPUT>` | Path to file to inspect (.safetensors, .gguf, .parquet, .csv)

## Options

Option | Description
--- | ---
`--mode <MODE>` | Inspection mode: summary, outliers, distribution, schema (default: summary)
`--columns <COLS>` | Specific columns to inspect (comma-separated)
`--z-threshold <Z>` | Z-score threshold for outlier detection (default: 3.0)
`-v, --verbose` | Show detailed tensor/column information

## Inspection Modes

### Summary Mode (default)

Display basic file statistics and metadata:

    entrenar inspect model.safetensors

Output:

    Inspecting: model.safetensors
      Mode: summary
    Model Information:
      File size: 125.42 MB
      Parameters: 0.03B
      Tensors: 48

### Outliers Mode

Detect statistical outliers using z-score:

    entrenar inspect data.parquet --mode outliers --z-threshold 2.5

Output:

    Inspecting: data.parquet
      Mode: outliers
    Outlier Detection (z-threshold: 2.5):
      Column 'loss': 12 outliers found
      Column 'accuracy': 3 outliers found

### Distribution Mode

Show distribution statistics for numeric columns:

    entrenar inspect data.parquet --mode distribution

### Schema Mode

Display schema information:

    entrenar inspect data.parquet --mode schema

## Supported Formats

Format | Extension | Information Shown
--- | --- | ---
SafeTensors | `.safetensors` | Tensor count, shapes, dtypes, total parameters
GGUF | `.gguf` | File size, format version
Parquet | `.parquet` | File size, column schema, row count
CSV | `.csv` | File size, column names

## Examples

### Inspect SafeTensors Model

    # Basic inspection
    entrenar inspect model.safetensors

    # Verbose output with tensor details
    entrenar inspect model.safetensors -v

Output with `-v`:

    Model Information:
      File size: 125.42 MB
      Parameters: 0.03B
      Tensors: 48

    Tensor Details:
      model.embed_tokens.weight: [32000, 4096] (F32)
      model.layers.0.self_attn.q_proj.weight: [4096, 4096] (F32)
      model.layers.0.self_attn.k_proj.weight: [4096, 4096] (F32)
      ... and 45 more tensors

### Inspect Training Data

    # Summary of parquet file
    entrenar inspect data/train.parquet

    # Detect outliers in specific columns
    entrenar inspect data/train.parquet --mode outliers --columns loss,accuracy

    # Show distribution statistics
    entrenar inspect data/train.parquet --mode distribution

### Inspect GGUF Model

    entrenar inspect model.gguf

Output:

    GGUF Model Information:
      File size: 4.12 GB
      Format: GGUF (llama.cpp compatible)
      (Use llama.cpp for detailed GGUF inspection)

## Programmatic Usage

    #![allow(unused)]
    fn main() {
    use entrenar::config::{load_config, InspectMode};
    use safetensors::SafeTensors;

    // Load and inspect SafeTensors
    let data = std::fs::read("model.safetensors")?;
    let tensors = SafeTensors::deserialize(&data)?;

    for name in tensors.names() {
        let tensor = tensors.tensor(name)?;
        println!("{}: {:?} ({:?})", name, tensor.shape(), tensor.dtype());
    }
    }

## See Also

- CLI Overview - General CLI reference
- Model I/O - Model formats and loading
- SafeTensors Format - SafeTensors specification