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Open in Google Colab

Free T4 GPU. No installation. Hit Run All.
The OBLITERATUS Colab notebook gives you a complete obliteration workflow in a free cloud environment — no local GPU, no installation, no setup. Open the notebook, select your model from the dropdown, pick a method, and hit Run All.

What you can do in Colab

Model selection

Pick any model from the built-in dropdown (populated from the 116-model registry), or type in any HuggingFace model ID directly.

Method selection

Choose from all available liberation methods: basic, advanced, aggressive, surgical, optimized, inverted, nuclear, or informed.

Download result

After obliteration completes, download the saved model as a ZIP directly to your local machine from the Colab file browser.

Push to Hub

Enter your HuggingFace token and target repo ID to push the obliterated model directly to your HuggingFace Hub account without downloading.

T4 GPU capabilities

Colab’s free tier provides an NVIDIA T4 with 15 GB of VRAM. This is sufficient for:
Colab Pro and Colab Pro+ give access to A100 GPUs (40 GB or 80 GB VRAM), which can handle models up to 70B with 4-bit quantization. The notebook works identically on any tier.

Pushing results to HuggingFace Hub

1

Generate a HuggingFace token

Go to your HuggingFace account settings → Access Tokens → New Token. Select write scope.
2

Create a target repository

Create a new model repository on HuggingFace Hub (e.g. your-username/llama-3-8b-obliterated). It can be private.
3

Enter credentials in the notebook

Paste your token and repo ID into the notebook’s Hub push cell. The notebook uses huggingface_hub.HfApi().upload_folder() internally.
4

Run the push cell

The obliterated model, tokenizer, and abliteration_metadata.json are all pushed to your repo. The metadata records the method, metrics, and pipeline configuration used.

Limitations

Colab free tier sessions have a maximum runtime of 12 hours and will disconnect after a period of inactivity. Large models (7B+) can take 20–60 minutes to obliterate depending on method and hardware. Save your results or push to Hub before the session ends.

When to use Colab vs. alternatives