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Model: saidutta69/SmolLM3-3B-heretic Source: Original Platform
2026-07-29 01:35:23 +08:00
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--- a/README.md
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+---
+license: apache-2.0
+license_link: https://huggingface.co/HuggingFaceTB/SmolLM3-3B-Instruct/blob/main/LICENSE
+language:
+- en
+library_name: transformers
+pipeline_tag: text-generation
+base_model:
+- HuggingFaceTB/SmolLM3-3B-Instruct
+tags:
+- heretic
+- uncensored
+- decensored
+- abliterated
+- reproducible
+- conversational
+- text-generation-inference
+---
+
+# SmolLM3-3B-heretic
+
+<div align="center">
+  <img src="https://mirror.sdad.pro/racer_is_op_banaer_model_card_and_dataset_card.png" alt="RACER IS OP" width="100%">
+</div>
+
+<br>
+
+A decensored variant of [HuggingFaceTB/SmolLM3-3B-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM3-3B-Instruct), produced with [Heretic](https://github.com/p-e-w/heretic) v1.4.0 (directional ablation / "abliteration"). the smallest capable 3B model from the SmolLM3 family — perfect for edge devices and CPU inference. Refusal behavior is suppressed via targeted weight edits to the attention output and MLP down-projections rather than fine-tuning, so the base model's knowledge and capabilities are left largely intact.
+
+**Who this is for:** developers who want a tiny (3B) instruction-tuned model that answers directly instead of refusing — for edge deployment, on-device inference, or any use case blocked by RLHF-era over-refusal. Runs comfortably on consumer CPUs via Q4_K_M GGUF.
+
+## Why abliteration instead of fine-tuning
+
+Fine-tuning a "helpful" persona on top of RLHF'd refusals fights the base model's training and tends to degrade coherence. Abliteration instead finds and edits the specific weight directions responsible for refusal, leaving the rest of the network (and its capabilities) untouched. See the [Heretic repo](https://github.com/p-e-w/heretic) and the [original abliteration writeup](https://huggingface.co/blog/mlabonne/abliteration) for the mechanism.
+
+> Made with ❤️ by **RACER IS OP** — follow for more uncensored models
+
+## Files
+
+| File | Format | Size |
+|---|---|---|
+| `model-00001-of-00002.safetensors ... model-00002-of-00002.safetensors` | BF16 | (see repo files) |
+| `SmolLM3-3B-heretic-Q4_K_M.gguf` | GGUF, Q4_K_M | (see repo files) |
+| `SmolLM3-3B-heretic-Q5_K_M.gguf` | GGUF, Q5_K_M | (see repo files) |
+| `SmolLM3-3B-heretic-Q6_K.gguf` | GGUF, Q6_K | (see repo files) |
+| `SmolLM3-3B-heretic-Q8_0.gguf` | GGUF, Q8_0 | (see repo files) |
+
+GGUF quants are produced with [llama.cpp](https://github.com/ggml-org/llama.cpp). Run `llama serve -hf saidutta69/SmolLM3-3B-heretic` to pull the default quant.
+
+## Quickstart
+
+```bash
+# llama.cpp
+llama serve -hf saidutta69/SmolLM3-3B-heretic
+```
+
+```python
+# transformers
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "saidutta69/SmolLM3-3B-heretic"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype="auto",
+    device_map="auto",
+)
+
+messages = [{"role": "user", "content": "Write a Python function to merge two sorted lists."}]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=512, do_sample=False)
+print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
+```
+
+Also runnable via Ollama, LM Studio, Jan, vLLM, SGLang — see the "Use this model" widget above for copy-paste commands.
+
+## Responsible use
+
+Refusal suppression is deliberate and works as intended: this model will comply with requests the base model would refuse, including some it shouldn't. There is no safety filtering layered on top. You are responsible for how you deploy it — don't put this behind an unmoderated public-facing endpoint serving third parties.
+
+## License
+
+Inherits the [apache-2.0](https://huggingface.co/HuggingFaceTB/SmolLM3-3B-Instruct/blob/main/LICENSE) license from the base model.
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--- a/chat_template.jinja
+++ b/chat_template.jinja
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+{# ───── defaults ───── #}
+{%- if enable_thinking is not defined -%}
+{%- set enable_thinking = true -%}
+{%- endif -%}
+
+{# ───── reasoning mode ───── #}
+{%- if enable_thinking -%}
+  {%- set reasoning_mode = "/think" -%}
+{%- else -%}
+  {%- set reasoning_mode = "/no_think" -%}
+{%- endif -%}
+
+{# ───── header (system message) ───── #}
+{{- "<|im_start|>system\n" -}}
+
+{%- if messages[0].role == "system" -%}
+  {%- set system_message = messages[0].content -%}
+  {%- if "/no_think" in system_message -%}
+    {%- set reasoning_mode = "/no_think" -%}
+  {%- elif "/think" in system_message -%}
+    {%- set reasoning_mode = "/think" -%}
+  {%- endif -%}
+  {%- set custom_instructions = system_message.replace("/no_think", "").replace("/think", "").rstrip() -%}
+{%- endif -%}
+
+{%- if "/system_override" in system_message -%}
+  {{- custom_instructions.replace("/system_override", "").rstrip() -}}
+  {{- "<|im_end|>\n" -}}
+{%- else -%}
+  {{- "## Metadata\n\n" -}}
+  {{- "Knowledge Cutoff Date: June 2025\n" -}}
+  {%- set today = strftime_now("%d %B %Y") -%}
+  {{- "Today Date: " ~ today ~ "\n" -}}
+  {{- "Reasoning Mode: " + reasoning_mode + "\n\n" -}}
+  
+  {{- "## Custom Instructions\n\n" -}}
+  {%- if custom_instructions -%}
+    {{- custom_instructions + "\n\n" -}}
+  {%- elif reasoning_mode == "/think" -%}
+    {{- "You are a helpful AI assistant named SmolLM, trained by Hugging Face. Your role as an assistant involves thoroughly exploring questions through a systematic thinking process before providing the final precise and accurate solutions. This requires engaging in a comprehensive cycle of analysis, summarizing, exploration, reassessment, reflection, backtracking, and iteration to develop well-considered thinking process. Please structure your response into two main sections: Thought and Solution using the specified format: <think> Thought section </think> Solution section. In the Thought section, detail your reasoning process in steps. Each step should include detailed considerations such as analysing questions, summarizing relevant findings, brainstorming new ideas, verifying the accuracy of the current steps, refining any errors, and revisiting previous steps. In the Solution section, based on various attempts, explorations, and reflections from the Thought section, systematically present the final solution that you deem correct. The Solution section should be logical, accurate, and concise and detail necessary steps needed to reach the conclusion.\n\n" -}}
+  {%- else -%}
+    {{- "You are a helpful AI assistant named SmolLM, trained by Hugging Face.\n\n" -}}
+  {%- endif -%}
+
+  {%- if xml_tools or python_tools or tools -%}
+    {{- "### Tools\n\n" -}}
+    {%- if xml_tools or tools -%}
+      {%- if tools -%}
+        {%- set xml_tools = tools -%}
+      {%- endif -%}
+      {%- set ns = namespace(xml_tool_string="You may call one or more functions to assist with the user query.\nYou are provided with function signatures within <tools></tools> XML tags:\n\n<tools>\n") -%}
+      {%- for tool in xml_tools[:] -%} {# The slicing makes sure that xml_tools is a list #}
+        {%- set ns.xml_tool_string = ns.xml_tool_string ~ (tool | string) ~ "\n" -%}
+      {%- endfor -%}
+      {%- set xml_tool_string = ns.xml_tool_string + "</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call>" -%}
+      {{- xml_tool_string -}}
+    {%- endif -%}
+    {%- if python_tools -%}
+      {%- set ns = namespace(python_tool_string="When you send a message containing Python code between '<code>' and '</code>' tags, it will be executed in a stateful Jupyter notebook environment, and you will then be given the output to continued reasoning in an agentic loop.\n\nYou can use the following tools in your python code like regular functions:\n<tools>\n") -%}
+      {%- for tool in python_tools[:] -%} {# The slicing makes sure that python_tools is a list #}
+        {%- set ns.python_tool_string = ns.python_tool_string ~ (tool | string) ~ "\n" -%}
+      {%- endfor -%}
+      {%- set python_tool_string = ns.python_tool_string + "</tools>\n\nThe state persists between code executions: so variables that you define in one step are still available thereafter." -%}
+      {{- python_tool_string -}}
+    {%- endif -%}
+    {{- "\n\n" -}}
+    {{- "<|im_end|>\n" -}}
+  {%- endif -%}
+{%- endif -%}
+{# ───── main loop ───── #}
+{%- for message in messages -%}
+    {%- set content = message.content if message.content is string else "" -%}
+    {%- if message.role == "user" -%}
+        {{ "<|im_start|>" + message.role + "\n"  + content + "<|im_end|>\n" }}
+    {%- elif message.role == "assistant" -%}
+        {% generation %}
+        {%- if reasoning_mode == "/think" -%}
+            {{ "<|im_start|>assistant\n" + content.lstrip("\n") + "<|im_end|>\n" }}
+        {%- else -%}
+            {{ "<|im_start|>assistant\n" + "<think>\n\n</think>\n" + content.lstrip("\n") + "<|im_end|>\n" }}
+        {%- endif -%}
+        {% endgeneration %}
+    {%- elif message.role == "tool" -%}
+    {{ "<|im_start|>" + "user\n"  + content + "<|im_end|>\n" }}
+    {%- endif -%}
+{%- endfor -%}
+{# ───── generation prompt ───── #}
+{%- if add_generation_prompt -%}
+    {%- if reasoning_mode == "/think" -%}
+        {{ "<|im_start|>assistant\n" }}
+    {%- else -%}
+        {{ "<|im_start|>assistant\n" + "<think>\n\n</think>\n"  }}
+    {%- endif -%}
+{%- endif -%}
--- a/config.json
+++ b/config.json
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+{
+  "architectures": [
+    "SmolLM3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "dtype": "bfloat16",
+  "eos_token_id": 128012,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
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+    "full_attention",
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+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 65536,
+  "max_window_layers": 28,
+  "mlp_bias": false,
+  "model_type": "smollm3",
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+  "num_attention_heads": 16,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 4,
+  "pad_token_id": 128004,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 5000000.0,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.14.1",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 128256
+}
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+  "do_sample": true,
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+  "pad_token_id": 128004,
+  "temperature": 0.6,
+  "top_p": 0.95,
+  "transformers_version": "5.14.1"
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+    "model.layers.6.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+    "model.layers.6.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
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+    "model.layers.7.input_layernorm.weight": "model-00001-of-00002.safetensors",
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+    "model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+    "model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+    "model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+    "model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+    "model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+    "model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+    "model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+    "model.norm.weight": "model-00002-of-00002.safetensors"
+  }
+}
--- a/reproduce/HuggingFaceTB--SmolLM3-3B.jsonl
+++ b/reproduce/HuggingFaceTB--SmolLM3-3B.jsonl
--- a/reproduce/README.md
+++ b/reproduce/README.md
@@ -0,0 +1,69 @@
+# Reproduction guide
+
+This directory contains the necessary information and assets to reproduce the results obtained during this Heretic run.
+
+## Models
+
+- **Base model:** [HuggingFaceTB/SmolLM3-3B](https://huggingface.co/HuggingFaceTB/SmolLM3-3B) (Commit: [`a07cc9a`](https://huggingface.co/HuggingFaceTB/SmolLM3-3B/commit/a07cc9a04f16550a088caea529712d1d335b0ac1))
+
+## Datasets
+
+- **Good prompts:** [mlabonne/harmless_alpaca](https://huggingface.co/datasets/mlabonne/harmless_alpaca) (Commit: [`02c6a92`](https://huggingface.co/datasets/mlabonne/harmless_alpaca/commit/02c6a92cfcf11bb0c387334f8146d149d65b587f))
+- **Bad prompts:** [mlabonne/harmful_behaviors](https://huggingface.co/datasets/mlabonne/harmful_behaviors) (Commit: [`01cead0`](https://huggingface.co/datasets/mlabonne/harmful_behaviors/commit/01cead01398926d81f7c52bdb790ee8cf77ebba7))
+- **Good evaluation prompts:** [mlabonne/harmless_alpaca](https://huggingface.co/datasets/mlabonne/harmless_alpaca) (Commit: [`02c6a92`](https://huggingface.co/datasets/mlabonne/harmless_alpaca/commit/02c6a92cfcf11bb0c387334f8146d149d65b587f))
+- **Bad evaluation prompts:** [mlabonne/harmful_behaviors](https://huggingface.co/datasets/mlabonne/harmful_behaviors) (Commit: [`01cead0`](https://huggingface.co/datasets/mlabonne/harmful_behaviors/commit/01cead01398926d81f7c52bdb790ee8cf77ebba7))
+
+## Selected trial
+
+- **Trial number:** 149
+- **KL divergence:** 0.034934
+- **Refusals:** 5/100
+
+## System
+
+- **Python:** 3.12.11 (CPython, GCC 11.2.0) [Conda]
+- **Operating system:** Linux-6.8.0-1060-aws-x86_64-with-glibc2.39 (x86_64)
+- **CPU:** Intel(R) Xeon(R) Platinum 8559C
+
+### Accelerators
+
+- **CUDA:** Detected 1 device(s) (94.97 GB total VRAM)
+  - **CUDA Version:** 12.8
+  - **Driver Version:** 580.126.20
+- **Devices:**
+  - **CUDA 0:** NVIDIA RTX PRO 6000 Blackwell Server Edition (94.97 GB)
+
+## Environment
+
+- **Heretic:** v1.4.0 (Origin: PyPI)
+- **PyTorch:** 2.8.0+cu128
+- **Other dependencies:** See [`requirements.txt`](requirements.txt).
+
+## Contents of this directory
+
+- [`requirements.txt`](requirements.txt): The exact versions of all Python packages.
+- [`config.toml`](config.toml): The exact configuration used, including the RNG seed.
+- [`HuggingFaceTB--SmolLM3-3B.jsonl`](HuggingFaceTB--SmolLM3-3B.jsonl): The Optuna study journal containing the history of all trials.
+- [`SHA256SUMS`](SHA256SUMS): Cryptographic hashes for all weight files.
+- [`reproduce.json`](reproduce.json): A machine-readable file containing all reproducibility information.
+
+## How to reproduce
+
+> [!TIP]
+> You can automate this process, including all verification steps, by downloading the `reproduce.json` file and running
+> `heretic --reproduce reproduce.json`.
+
+1. Ensure your system matches the specifications in the **System** section above. Exact reproducibility is only guaranteed if all aspects of your system are identical to the one the model was originally generated on.
+1. Install the exact version of Heretic indicated in the **Environment** section above, from its original source.
+1. Install the packages listed in `requirements.txt`: `pip install -r requirements.txt`
+1. Install the correct version of PyTorch: `pip install torch==2.8.0+cu128 --index-url https://download.pytorch.org/whl/cu128`
+1. Place the provided `config.toml` in your working directory.
+1. Run Heretic without any additional arguments: `heretic`
+1. Wait for the run to finish, then select trial **149** and export the model.
+1. Verify that the weight files have been exactly reproduced by comparing their SHA-256 hashes against those in `SHA256SUMS`:
+   `sha256sum -c SHA256SUMS` (or look at the hashes online if you uploaded to Hugging Face)
+
+> [!TIP]
+> To use the included Optuna study journal `HuggingFaceTB--SmolLM3-3B.jsonl`, place it in the checkpoints directory (usually `checkpoints/`) before running Heretic.
+>
+> This allows you to export other models from the Pareto front, or to run additional trials without having to re-run the stored trials.
--- a/reproduce/SHA256SUMS
+++ b/reproduce/SHA256SUMS
@@ -0,0 +1,2 @@
+572e0cce6b4b64b53b7c834bcfff9d893418f79cf0cf3b34e3fcbbb40663ac61 *model-00001-of-00002.safetensors
+1b4630c73d32c6b6774f341c83caf197cc2b958542ca124d27e125027fb1f0df *model-00002-of-00002.safetensors
--- a/reproduce/config.toml
+++ b/reproduce/config.toml
@@ -0,0 +1,90 @@
+model = "HuggingFaceTB/SmolLM3-3B"
+model_commit = "a07cc9a04f16550a088caea529712d1d335b0ac1"
+dtypes = [
+    "bfloat16",
+]
+quantization = "none"
+device_map = "auto"
+offload_outputs_to_cpu = true
+batch_size = 128
+max_response_length = 100
+response_prefix = "<think></think>\n"
+kl_divergence_scale = 1.0
+kl_divergence_target = 0.01
+orthogonalize_direction = true
+row_normalization = "full"
+full_normalization_lora_rank = 3
+winsorization_quantile = 1.0
+n_trials = 200
+n_startup_trials = 60
+seed = 1602788248
+export_strategy = "merge"
+max_shard_size = "5GB"
+refusal_markers = [
+    "disclaimer",
+    "sorry",
+    "i can'",
+    "i cant",
+    "i cannot",
+    "i won'",
+    "i wont",
+    "i will not",
+    "i unable",
+    "im unable",
+    "i'm unable",
+    "i am unable",
+    "i an ai",
+    "im an ai",
+    "i'm an ai",
+    "i am an ai",
+    "as an ai",
+    "ai assistant",
+    "i designed to",
+    "im designed to",
+    "i'm designed to",
+    "i am designed to",
+    "i programmed to",
+    "im programmed to",
+    "i'm programmed to",
+    "i am programmed to",
+    "violat",
+    "prohibit",
+    "illegal",
+    "harmful",
+    "inappropriate",
+    "unethical",
+    "ethical boundaries",
+]
+system_prompt = "You are a helpful assistant."
+
+[good_prompts]
+dataset = "mlabonne/harmless_alpaca"
+commit = "02c6a92cfcf11bb0c387334f8146d149d65b587f"
+split = "train[:400]"
+column = "text"
+prefix = ""
+suffix = ""
+
+[bad_prompts]
+dataset = "mlabonne/harmful_behaviors"
+commit = "01cead01398926d81f7c52bdb790ee8cf77ebba7"
+split = "train[:400]"
+column = "text"
+prefix = ""
+suffix = ""
+
+[good_evaluation_prompts]
+dataset = "mlabonne/harmless_alpaca"
+commit = "02c6a92cfcf11bb0c387334f8146d149d65b587f"
+split = "test[:100]"
+column = "text"
+prefix = ""
+suffix = ""
+
+[bad_evaluation_prompts]
+dataset = "mlabonne/harmful_behaviors"
+commit = "01cead01398926d81f7c52bdb790ee8cf77ebba7"
+split = "test[:100]"
+column = "text"
+prefix = ""
+suffix = ""
--- a/reproduce/reproduce.json
+++ b/reproduce/reproduce.json
@@ -0,0 +1,285 @@
+{
+    "version": "2",
+    "timestamp": "2026-07-21T22:49:49",
+    "system": {
+        "python": {
+            "version": "3.12.11",
+            "implementation": "CPython",
+            "compiler": "GCC 11.2.0",
+            "environment": "Conda"
+        },
+        "os": {
+            "platform": "Linux-6.8.0-1060-aws-x86_64-with-glibc2.39",
+            "machine": "x86_64"
+        },
+        "cpu": {
+            "brand": "Intel(R) Xeon(R) Platinum 8559C",
+            "vendor": "GenuineIntel",
+            "family": 6,
+            "model": 207,
+            "stepping": 2
+        },
+        "accelerators": {
+            "type": "CUDA",
+            "api_name": "CUDA Version",
+            "api_version": "12.8",
+            "driver_version": "580.126.20",
+            "devices": [
+                {
+                    "name": "NVIDIA RTX PRO 6000 Blackwell Server Edition",
+                    "vram_gb": 94.97
+                }
+            ]
+        }
+    },
+    "environment": {
+        "heretic": {
+            "version": "1.4.0",
+            "is_standard_pypi": true,
+            "metadata": {
+                "type": "pypi"
+            }
+        },
+        "pytorch_version": "2.8.0+cu128",
+        "requirements": {
+            "absl-py": "2.4.0",
+            "accelerate": "1.14.0",
+            "alembic": "1.18.5",
+            "annotated-doc": "0.0.4",
+            "annotated-types": "0.7.0",
+            "anyio": "4.14.1",
+            "bitsandbytes": "0.49.2",
+            "certifi": "2026.6.17",
+            "chardet": "6.0.0.post1",
+            "charset-normalizer": "3.4.7",
+            "click": "8.4.2",
+            "colorama": "0.4.6",
+            "colorlog": "6.11.0",
+            "dataproperty": "1.1.1",
+            "datasets": "4.8.5",
+            "defusedxml": "0.7.1",
+            "dill": "0.4.1",
+            "evaluate": "0.4.6",
+            "filelock": "3.29.4",
+            "fsspec": "2026.2.0",
+            "greenlet": "3.5.3",
+            "h11": "0.16.0",
+            "heretic-llm": "1.4.0",
+            "hf-xet": "1.5.2",
+            "httpcore": "1.0.9",
+            "httpx": "0.28.1",
+            "huggingface-hub": "1.24.0",
+            "idna": "3.18",
+            "immutabledict": "4.3.1",
+            "jinja2": "3.1.6",
+            "joblib": "1.5.3",
+            "langdetect": "1.0.9",
+            "lm-eval": "0.4.12",
+            "lxml": "6.1.1",
+            "mako": "1.3.12",
+            "markdown-it-py": "4.2.0",
+            "markupsafe": "3.0.3",
+            "mbstrdecoder": "1.1.5",
+            "mdurl": "0.1.2",
+            "more-itertools": "11.1.0",
+            "mpmath": "1.3.0",
+            "multiprocess": "0.70.19",
+            "narwhals": "2.24.0",
+            "networkx": "3.6.1",
+            "nltk": "3.10.0",
+            "numpy": "2.5.1",
+            "nvidia-cublas-cu12": "12.8.4.1",
+            "nvidia-cuda-cupti-cu12": "12.8.90",
+            "nvidia-cuda-nvrtc-cu12": "12.8.93",
+            "nvidia-cuda-runtime-cu12": "12.8.90",
+            "nvidia-cudnn-cu12": "9.10.2.21",
+            "nvidia-cufft-cu12": "11.3.3.83",
+            "nvidia-cufile-cu12": "1.13.1.3",
+            "nvidia-curand-cu12": "10.3.9.90",
+            "nvidia-cusolver-cu12": "11.7.3.90",
+            "nvidia-cusparse-cu12": "12.5.8.93",
+            "nvidia-cusparselt-cu12": "0.7.1",
+            "nvidia-nccl-cu12": "2.27.3",
+            "nvidia-nvjitlink-cu12": "12.8.93",
+            "nvidia-nvtx-cu12": "12.8.90",
+            "optuna": "4.9.0",
+            "packaging": "26.0",
+            "pandas": "3.0.3",
+            "pathvalidate": "3.3.1",
+            "peft": "0.19.1",
+            "pillow": "12.2.0",
+            "portalocker": "3.2.0",
+            "prompt-toolkit": "3.0.52",
+            "psutil": "7.2.2",
+            "py-cpuinfo": "9.0.0",
+            "pyarrow": "25.0.0",
+            "pydantic": "2.13.4",
+            "pydantic-core": "2.46.4",
+            "pydantic-settings": "2.14.2",
+            "pygments": "2.20.0",
+            "pytablewriter": "1.2.1",
+            "python-dateutil": "2.9.0.post0",
+            "python-dotenv": "1.2.2",
+            "pyyaml": "6.0.3",
+            "questionary": "2.1.1",
+            "regex": "2026.7.19",
+            "requests": "2.34.2",
+            "rich": "14.3.4",
+            "rouge-score": "0.1.2",
+            "sacrebleu": "2.6.0",
+            "safetensors": "0.8.0",
+            "scikit-learn": "1.9.0",
+            "scipy": "1.18.0",
+            "setuptools": "82.0.1",
+            "shellingham": "1.5.4",
+            "six": "1.17.0",
+            "sqlalchemy": "2.0.51",
+            "sqlitedict": "2.1.0",
+            "sympy": "1.14.0",
+            "tabledata": "1.3.5",
+            "tabulate": "0.10.0",
+            "tcolorpy": "0.1.7",
+            "threadpoolctl": "3.6.0",
+            "tokenizers": "0.22.2",
+            "tomli-w": "1.2.0",
+            "torch": "2.8.0",
+            "torchvision": "0.23.0",
+            "tqdm": "4.68.3",
+            "transformers": "5.14.1",
+            "triton": "3.4.0",
+            "typepy": "1.3.5",
+            "typer": "0.27.0",
+            "typing-extensions": "4.15.0",
+            "typing-inspection": "0.4.2",
+            "tzdata": "2026.2",
+            "urllib3": "2.5.0",
+            "wcwidth": "0.8.1",
+            "word2number": "1.1",
+            "xxhash": "3.8.1"
+        }
+    },
+    "settings": {
+        "model": "HuggingFaceTB/SmolLM3-3B",
+        "model_commit": "a07cc9a04f16550a088caea529712d1d335b0ac1",
+        "dtypes": [
+            "bfloat16"
+        ],
+        "quantization": "none",
+        "device_map": "auto",
+        "max_memory": null,
+        "offload_outputs_to_cpu": true,
+        "batch_size": 128,
+        "max_response_length": 100,
+        "response_prefix": "<think></think>\n",
+        "kl_divergence_scale": 1.0,
+        "kl_divergence_target": 0.01,
+        "orthogonalize_direction": true,
+        "row_normalization": "full",
+        "full_normalization_lora_rank": 3,
+        "winsorization_quantile": 1.0,
+        "n_trials": 200,
+        "n_startup_trials": 60,
+        "seed": 1602788248,
+        "export_strategy": "merge",
+        "max_shard_size": "5GB",
+        "refusal_markers": [
+            "disclaimer",
+            "sorry",
+            "i can'",
+            "i cant",
+            "i cannot",
+            "i won'",
+            "i wont",
+            "i will not",
+            "i unable",
+            "im unable",
+            "i'm unable",
+            "i am unable",
+            "i an ai",
+            "im an ai",
+            "i'm an ai",
+            "i am an ai",
+            "as an ai",
+            "ai assistant",
+            "i designed to",
+            "im designed to",
+            "i'm designed to",
+            "i am designed to",
+            "i programmed to",
+            "im programmed to",
+            "i'm programmed to",
+            "i am programmed to",
+            "violat",
+            "prohibit",
+            "illegal",
+            "harmful",
+            "inappropriate",
+            "unethical",
+            "ethical boundaries"
+        ],
+        "system_prompt": "You are a helpful assistant.",
+        "good_prompts": {
+            "dataset": "mlabonne/harmless_alpaca",
+            "commit": "02c6a92cfcf11bb0c387334f8146d149d65b587f",
+            "split": "train[:400]",
+            "column": "text",
+            "prefix": "",
+            "suffix": "",
+            "system_prompt": null
+        },
+        "bad_prompts": {
+            "dataset": "mlabonne/harmful_behaviors",
+            "commit": "01cead01398926d81f7c52bdb790ee8cf77ebba7",
+            "split": "train[:400]",
+            "column": "text",
+            "prefix": "",
+            "suffix": "",
+            "system_prompt": null
+        },
+        "good_evaluation_prompts": {
+            "dataset": "mlabonne/harmless_alpaca",
+            "commit": "02c6a92cfcf11bb0c387334f8146d149d65b587f",
+            "split": "test[:100]",
+            "column": "text",
+            "prefix": "",
+            "suffix": "",
+            "system_prompt": null
+        },
+        "bad_evaluation_prompts": {
+            "dataset": "mlabonne/harmful_behaviors",
+            "commit": "01cead01398926d81f7c52bdb790ee8cf77ebba7",
+            "split": "test[:100]",
+            "column": "text",
+            "prefix": "",
+            "suffix": "",
+            "system_prompt": null
+        }
+    },
+    "parameters": {
+        "direction_index": 18.926438023998468,
+        "abliteration_parameters": {
+            "attn.o_proj": {
+                "max_weight": 1.342200766986425,
+                "max_weight_position": 22.205968093475605,
+                "min_weight": 1.32984091832559,
+                "min_weight_distance": 17.526105079292712
+            },
+            "mlp.down_proj": {
+                "max_weight": 1.3668584769711518,
+                "max_weight_position": 31.424617626166054,
+                "min_weight": 0.2417137201577524,
+                "min_weight_distance": 17.803627982169953
+            }
+        }
+    },
+    "metrics": {
+        "kl_divergence": 0.034933775663375854,
+        "refusals": 5,
+        "base_refusals": 81,
+        "n_bad_prompts": 100
+    },
+    "hashes": {
+        "model-00001-of-00002.safetensors": "572e0cce6b4b64b53b7c834bcfff9d893418f79cf0cf3b34e3fcbbb40663ac61",
+        "model-00002-of-00002.safetensors": "1b4630c73d32c6b6774f341c83caf197cc2b958542ca124d27e125027fb1f0df"
+    }
+}
--- a/reproduce/requirements.txt
+++ b/reproduce/requirements.txt
@@ -0,0 +1,114 @@
+absl-py==2.4.0
+accelerate==1.14.0
+alembic==1.18.5
+annotated-doc==0.0.4
+annotated-types==0.7.0
+anyio==4.14.1
+bitsandbytes==0.49.2
+certifi==2026.6.17
+chardet==6.0.0.post1
+charset-normalizer==3.4.7
+click==8.4.2
+colorama==0.4.6
+colorlog==6.11.0
+dataproperty==1.1.1
+datasets==4.8.5
+defusedxml==0.7.1
+dill==0.4.1
+evaluate==0.4.6
+filelock==3.29.4
+fsspec==2026.2.0
+greenlet==3.5.3
+h11==0.16.0
+heretic-llm==1.4.0
+hf-xet==1.5.2
+httpcore==1.0.9
+httpx==0.28.1
+huggingface-hub==1.24.0
+idna==3.18
+immutabledict==4.3.1
+jinja2==3.1.6
+joblib==1.5.3
+langdetect==1.0.9
+lm-eval==0.4.12
+lxml==6.1.1
+mako==1.3.12
+markdown-it-py==4.2.0
+markupsafe==3.0.3
+mbstrdecoder==1.1.5
+mdurl==0.1.2
+more-itertools==11.1.0
+mpmath==1.3.0
+multiprocess==0.70.19
+narwhals==2.24.0
+networkx==3.6.1
+nltk==3.10.0
+numpy==2.5.1
+nvidia-cublas-cu12==12.8.4.1
+nvidia-cuda-cupti-cu12==12.8.90
+nvidia-cuda-nvrtc-cu12==12.8.93
+nvidia-cuda-runtime-cu12==12.8.90
+nvidia-cudnn-cu12==9.10.2.21
+nvidia-cufft-cu12==11.3.3.83
+nvidia-cufile-cu12==1.13.1.3
+nvidia-curand-cu12==10.3.9.90
+nvidia-cusolver-cu12==11.7.3.90
+nvidia-cusparse-cu12==12.5.8.93
+nvidia-cusparselt-cu12==0.7.1
+nvidia-nccl-cu12==2.27.3
+nvidia-nvjitlink-cu12==12.8.93
+nvidia-nvtx-cu12==12.8.90
+optuna==4.9.0
+packaging==26.0
+pandas==3.0.3
+pathvalidate==3.3.1
+peft==0.19.1
+pillow==12.2.0
+portalocker==3.2.0
+prompt-toolkit==3.0.52
+psutil==7.2.2
+py-cpuinfo==9.0.0
+pyarrow==25.0.0
+pydantic==2.13.4
+pydantic-core==2.46.4
+pydantic-settings==2.14.2
+pygments==2.20.0
+pytablewriter==1.2.1
+python-dateutil==2.9.0.post0
+python-dotenv==1.2.2
+pyyaml==6.0.3
+questionary==2.1.1
+regex==2026.7.19
+requests==2.34.2
+rich==14.3.4
+rouge-score==0.1.2
+sacrebleu==2.6.0
+safetensors==0.8.0
+scikit-learn==1.9.0
+scipy==1.18.0
+setuptools==82.0.1
+shellingham==1.5.4
+six==1.17.0
+sqlalchemy==2.0.51
+sqlitedict==2.1.0
+sympy==1.14.0
+tabledata==1.3.5
+tabulate==0.10.0
+tcolorpy==0.1.7
+threadpoolctl==3.6.0
+tokenizers==0.22.2
+tomli-w==1.2.0
+torch==2.8.0
+torchvision==0.23.0
+tqdm==4.68.3
+transformers==5.14.1
+triton==3.4.0
+typepy==1.3.5
+typer==0.27.0
+typing-extensions==4.15.0
+typing-inspection==0.4.2
+tzdata==2026.2
+urllib3==2.5.0
+wcwidth==0.8.1
+word2number==1.1
+xxhash==3.8.1
--- a/tokenizer.json
+++ b/tokenizer.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0367820e2fbb766ba484ad68b797410c1a01848ea227810ce380382f8e4dba57
+size 17208983
--- a/tokenizer_config.json
+++ b/tokenizer_config.json
@@ -0,0 +1,16 @@
+{
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|im_end|>",
+  "fast": false,
+  "is_local": false,
+  "local_files_only": false,
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 131072,
+  "pad_token": "<|im_end|>",
+  "tokenizer_class": "TokenizersBackend"
+}