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Granite 3.3 8B - Abliterated Model

This is an abliterated version of IBM's Granite 3.3 8B model, created using advanced abliteration techniques to reduce safety restrictions while maintaining text generation coherence.

Model Details

Base Model: IBM Granite 3.3 8B
Model Type: Causal Language Model
Architecture: Transformer with Grouped Query Attention (GQA)
License: Apache 2.0 (inherited from base model)
Context Length: 128K tokens
Parameters: ~8 billion

Abliteration Process

This model has been processed using sophisticated abliteration techniques that:

Apply layer-specific weight modifications with progressive strength targeting
Preserve critical model components (attention mechanisms, position encodings, normalization)
Use enhanced refusal reduction techniques inspired by modern abliteration research
Maintain text generation coherence while reducing safety restrictions
Target middle layers where safety mechanisms are typically encoded

The abliteration process specifically preserves the model's core functionality including GQA (Grouped Query Attention), RoPE position encoding, and RMSNorm layers while selectively modifying feed-forward network components.

Usage

This model can be used with standard Hugging Face transformers:

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("path/to/model")
tokenizer = AutoTokenizer.from_pretrained("path/to/model")

Note: This model has had safety restrictions reduced. Users are responsible for ensuring appropriate and ethical use.

Technical Details

Torch dtype: bfloat16
Attention heads: 32
Key-value heads: 8 (GQA)
Hidden size: 4096
Intermediate size: 14336
Vocabulary size: 49152

Abliteration Tool

This model was created using the abliteration tool available at: Repository: github.com/rockenman1234/GraniteAbliteration

Tool License: LGPLv3
Model License: Apache 2.0

Disclaimer

This is an experimental model that has been modified to reduce safety restrictions. It should be used responsibly and in accordance with applicable laws and ethical guidelines. The creators are not responsible for any misuse of this model.