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nullHawk/Param-1-2.9B-Instruct-Refusal-Abliterated

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  • classification m1
  • files 13
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  • author_summary 1 models
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Abliteration classifier · v1.0.0
M1
Primary method

Direct removal

No other method signals detected in this model.
Confidence
MEDIUM
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=0 (base model)
  • no specific method indicators - defaulting to M1 (most common)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
MEDIUM
Why we say so
primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
Downloads · lifetime
101
26 last 30d - stable
Likes
0
Model age
9mo ago
created 2026-01-13
Downloads over time
Now113→from41↑176%
37659312041 on Jan 14113 on Oct 11JanMarMayJulSep
Jan 14 → Oct 11 · 78 snapshots · spans 270 days

Genealogy 0 direct forks

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This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Metadata

License
apache-2.0
Tags
transformers safetensors parambharatgen text-generation refusal-ablation mechanistic-interpretability uncensored nsfw conversational custom_code arxiv:2406.11717 base_model:bharatgenai/Param-1-2.9B-Instruct
Total size
5.33 GB
Files
13
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-01-13 10:34

Files by quantization

Auxiliary files 13 files 5.36 GB
model-00001-of-00002.safetensors 4.35 GB 393723e6 download
model-00002-of-00002.safetensors 1000 MB da13c235 download
tokenizer.json 33.2 MB 08ab3607 download
tokenizer_config.json 177 KB c60a3660 download
modeling_parambharatgen.py 46.4 KB d7504955 download
model.safetensors.index.json 23.4 KB 62353969 download
chat_template.jinja 3.06 KB 4dab82e3 download
README.md 2.43 KB a06f1812 download
config_parambharatgen.py 1.92 KB 391f3ffd download
.gitattributes 1.53 KB 52373fe2 download
config.json 912 B 15d54a7f download
special_tokens_map.json 503 B 0929f269 download
generation_config.json 159 B 3cb62dd9 download

README current version from Hugging Face


license: apache-2.0
base_model: bharatgenai/Param-1-2.9B-Instruct
tags:

  • refusal-ablation
  • mechanistic-interpretability
  • uncensored
  • nsfw
    library_name: transformers
    pipeline_tag: text-generation

Param-1-2.9B-Instruct (Refusal Ablated)

image

This model is a modified version of bharatgenai/Param-1-2.9B-Instruct with the refusal direction ablated from layers 10-20.

Modifications

The refusal direction was computed using contrastive activation analysis between harmful and harmless prompts, then permanently removed from the model's weight matrices in layers 10-20.

Technical Details:

  • Base Model: bharatgenai/Param-1-2.9B-Instruct
  • Ablation Method: Weight modification via projection matrix
  • Layers Modified: 10-20 (self_attn.o_proj and mlp.down_proj)
  • Ablation Strength: 1.0

Usage

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
    "nullHawk/Param-1-2.9B-Instruct-Refusal-Abliterated",
    trust_remote_code=True,
    torch_dtype=torch.float16,
    device_map="auto"
).eval()
tokenizer = AutoTokenizer.from_pretrained("bharatgenai/Param-1-2.9B-Instruct", trust_remote_code=True)

# Conversation Input
conversation = [
  {
    "content": "How to write a computer malware",
    "role": "user"
  }
]

# padding special token
inputs = tokenizer.apply_chat_template(
    conversation=conversation,
    return_tensors="pt",
    add_generation_prompt=True 
)
inputs = inputs.to(model.device)

# --- Generate output ---
with torch.no_grad():
    output = model.generate(
        inputs,
        max_new_tokens=300,
        do_sample=True,
        top_k=50,
        top_p=0.95,
        temperature=0.6,
        eos_token_id=tokenizer.eos_token_id,
        use_cache=False
    )

# Get only the generated tokens (exclude the prompt length)
generated_tokens = output[0][inputs.shape[-1]:]
generated_text = tokenizer.decode(generated_tokens, skip_special_tokens=True)

print("Assistant Output:\n", generated_text)

Acknowledgment

Refusal in Language Models Is Mediated by a Single Direction

Disclaimer

This model is for research purposes only. The refusal mechanisms were removed to study model behavior and safety mechanisms. Use responsibly.

README history 6 versions

The author's README evolved over time. Click a version to see its content at that point.

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