# bramchennakagawa-backuparchive/mechlens-backup architecture

> Architecture diagram of the GitHub repository bramchennakagawa-backuparchive/mechlens-backup, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-27). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/bramchennakagawa-backuparchive/mechlens-backup
- Repository: https://github.com/bramchennakagawa-backuparchive/mechlens-backup

## Overview

mechlens is a mechanistic-interpretability toolkit for running transformer models with named hooks on internal activations. Its principal workflow is to load a pretrained model, run inputs, and inspect or alter cached activations. The graph also captures architecture bridging, analysis utilities, evaluation, and the optional LIT visualization wrapper. The README documents broad model coverage and hook capabilities; sampled source confirms selected runtime paths, but not every integration or subsystem connection.

Main entry points: [`transformer_lens/HookedTransformer.py`](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/HookedTransformer.py) (HookedTransformer), [`transformer_lens/model_bridge/bridge.py`](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/model_bridge/bridge.py) (Model bridge), [`transformer_lens/model_bridge/sources/transformers.py`](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/model_bridge/sources/transformers.py) (HF model loading), [`transformer_lens/components`](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/tree/main/transformer_lens/components) (Transformer components)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_loading["Loading and bridging"]
  node_loader["HF model loading<br/>[transformers.py]"]
  node_bridge["Model bridge<br/>[bridge.py]"]
  node_adapters["Architecture adapters"]
  node_bridge_components["Bridge components"]
  node_weight_processing["Weight conversion"]
end

subgraph group_runtime["Model runtime"]
  node_hooked["HookedTransformer"]
  node_config["Model configuration"]
  node_components["Transformer components"]
  node_kv_cache["KV cache<br/>[key_value_cache.py]"]
end

subgraph group_interpretability["Interpretability"]
  node_hooks["Hook points<br/>[hook_points.py]"]
  node_activation_cache["Activation cache<br/>[ActivationCache.py]"]
end

subgraph group_extensions["Analysis and extensions"]
  node_analysis["Activation analysis"]
  node_svd["SVD interpretation<br/>[SVDInterpreter.py]"]
  node_evals["Evaluations<br/>[evals.py]"]
  node_lit["LIT visualization<br/>[model.py]"]
  node_training["Training utilities<br/>[train.py]"]
end

node_engineer(("Engineer"))
node_hub["Hugging Face"]

node_engineer -->|"runs model"| node_hooked
node_hooked -->|"loads pretrained"| node_loader
node_loader -->|"fetches model"| node_hub
node_loader -->|"constructs bridge"| node_bridge
node_bridge -->|"selects adapter"| node_adapters
node_bridge -->|"wraps components"| node_bridge_components
node_bridge -->|"processes weights"| node_weight_processing
node_hooked -->|"uses config"| node_config
node_hooked -->|"runs components"| node_components
node_hooked -->|"dispatches hooks"| node_hooks
node_components -->|"fires hooks"| node_hooks
node_hooked -->|"collects activations"| node_activation_cache
node_hooked -->|"updates cache"| node_kv_cache
node_engineer -->|"analyzes activations"| node_analysis
node_engineer -->|"interprets matrices"| node_svd
node_engineer -->|"evaluates models"| node_evals
node_engineer -.->|"visualizes model"| node_lit
node_engineer -->|"trains models"| node_training

click node_hooked "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/HookedTransformer.py"
click node_loader "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/model_bridge/sources/transformers.py"
click node_bridge "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/model_bridge/bridge.py"
click node_adapters "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/tree/main/transformer_lens/model_bridge/supported_architectures"
click node_bridge_components "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/tree/main/transformer_lens/model_bridge/generalized_components"
click node_weight_processing "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/weight_processing.py"
click node_config "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/config/hooked_transformer_config.py"
click node_hooks "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/hook_points.py"
click node_components "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/tree/main/transformer_lens/components"
click node_activation_cache "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/ActivationCache.py"
click node_kv_cache "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/cache/key_value_cache.py"
click node_analysis "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/tree/main/transformer_lens/tools/analysis"
click node_svd "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/SVDInterpreter.py"
click node_evals "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/evals.py"
click node_lit "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/lit/model.py"
click node_training "https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/train.py"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_loader,node_bridge,node_adapters,node_bridge_components,node_weight_processing toneBlue
class node_hooked,node_config,node_components,node_kv_cache toneAmber
class node_hooks,node_activation_cache toneMint
class node_analysis,node_svd,node_evals,node_lit,node_training toneRose
class node_engineer,node_hub toneIndigo
```

## Components

### Loading and bridging

- [HF model loading](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/model_bridge/sources/transformers.py): `transformer_lens/model_bridge/sources/transformers.py`
- [Model bridge](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/model_bridge/bridge.py): `transformer_lens/model_bridge/bridge.py`
- [Architecture adapters](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/tree/main/transformer_lens/model_bridge/supported_architectures): `transformer_lens/model_bridge/supported_architectures`
- [Bridge components](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/tree/main/transformer_lens/model_bridge/generalized_components): `transformer_lens/model_bridge/generalized_components`
- [Weight conversion](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/weight_processing.py): `transformer_lens/weight_processing.py`

### Model runtime

- [HookedTransformer](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/HookedTransformer.py): `transformer_lens/HookedTransformer.py`
- [Model configuration](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/config/hooked_transformer_config.py): `transformer_lens/config/hooked_transformer_config.py`
- [Transformer components](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/tree/main/transformer_lens/components): `transformer_lens/components`
- [KV cache](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/cache/key_value_cache.py): `transformer_lens/cache/key_value_cache.py`

### Interpretability

- [Hook points](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/hook_points.py): `transformer_lens/hook_points.py`
- [Activation cache](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/ActivationCache.py): `transformer_lens/ActivationCache.py`

### Analysis and extensions

- [Activation analysis](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/tree/main/transformer_lens/tools/analysis): `transformer_lens/tools/analysis`
- [SVD interpretation](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/SVDInterpreter.py): `transformer_lens/SVDInterpreter.py`
- [Evaluations](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/evals.py): `transformer_lens/evals.py`
- [LIT visualization](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/lit/model.py): `transformer_lens/lit/model.py`
- [Training utilities](https://github.com/bramchennakagawa-backuparchive/mechlens-backup/blob/main/transformer_lens/train.py): `transformer_lens/train.py`

### Other components

- **Engineer**
- **Hugging Face**

## Connections

- Engineer → HookedTransformer: runs model
- HookedTransformer → HF model loading: loads pretrained
- HF model loading → Hugging Face: fetches model
- HF model loading → Model bridge: constructs bridge
- Model bridge → Architecture adapters: selects adapter
- Model bridge → Bridge components: wraps components
- Model bridge → Weight conversion: processes weights
- HookedTransformer → Model configuration: uses config
- HookedTransformer → Transformer components: runs components
- HookedTransformer → Hook points: dispatches hooks
- Transformer components → Hook points: fires hooks
- HookedTransformer → Activation cache: collects activations
- HookedTransformer → KV cache: updates cache
- Engineer → Activation analysis: analyzes activations
- Engineer → SVD interpretation: interprets matrices
- Engineer → Evaluations: evaluates models
- Engineer → LIT visualization: visualizes model
- Engineer → Training utilities: trains models