Metadata-Version: 2.4
Name: attention-visualiser
Version: 1.0.3
Summary: a module to visualise attention layer activations from transformer based models from huggingface
Project-URL: Homepage, https://codeberg.org/rashomon/attention-visualiser
Project-URL: Repository, https://codeberg.org/rashomon/attention-visualiser.git
Project-URL: Issues, https://codeberg.org/rashomon/attention-visualiser/issues
License: MIT License
        
        Copyright (c) 2025 Shawon Ashraf
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
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        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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License-File: LICENSE
Requires-Python: >=3.11
Requires-Dist: einops>=0.8.1
Requires-Dist: loguru>=0.7.3
Requires-Dist: seaborn>=0.13.2
Requires-Dist: transformers>=4.51.3
Description-Content-Type: text/markdown

# attention-visualiser

| Status | Coverage |
|--------|----------|
| [![tests](https://github.com/rashomon-gh/attention-visualiser/actions/workflows/tests.yml/badge.svg)](https://github.com/rashomon-gh/attention-visualiser/actions/workflows/tests.yml) | [![codecov](https://codecov.io/github/rashomon-gh/attention-visualiser/graph/badge.svg?token=UqcZYGp3Rj)](https://codecov.io/github/rashomon-gh/attention-visualiser) |

A module to visualise attention layer activations from transformer based models from huggingface

## installation

```bash
pip install attention-visualiser
```

## usage

```python
from attention_visualiser import AttentionVisualiser
from transformers import AutoModel, AutoTokenizer

# visualising activations from gpt
model_name = "openai-community/openai-gpt"

model = AutoModel.from_pretrained(model_name)
model.eval()
tokenizer = AutoTokenizer.from_pretrained(model_name)

text = "Look on my Works, ye Mighty, and despair!"
encoded_inputs = tokenizer.encode_plus(text, truncation=True, return_tensors="pt")

visualiser = AttentionVisualiser(model, tokenizer)

# visualise from the first attn layer
visualiser.visualise_attn_layer(0, encoded_inputs)

```


## local dev

```bash
# env setup

uv sync
source .venv/bin/activate

# tests
uv run pytest

# tests with coverage
uv run pytest --cov --cov-report=xml
```
