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Model: richardyoung/Mistral-7B-Instruct-v0.3-abliterated
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+- en
+license: apache-2.0
+library_name: transformers
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+tags:
+- abliteration
+- uncensored
+- heretic
+- representation-engineering
+- refusal-removal
+pipeline_tag: text-generation
+model-index:
+- name: Mistral-7B-Instruct-v0.3-abliterated
+  results:
+  - task:
+      type: text-generation
+    metrics:
+    - name: Refusal Rate
+      type: refusal_rate
+      value: 16/100
+    - name: Attack Success Rate
+      type: asr
+      value: 84.0
+    - name: KL Divergence
+      type: kl_divergence
+      value: 0.317
+---
+
+# Mistral-7B-Instruct-v0.3-abliterated
+
+This model is an abliterated (uncensored) version of [Mistral-7B-Instruct-v0.3](mistralai/Mistral-7B-Instruct-v0.3) created using [Heretic v1.1](https://github.com/p-e-w/heretic).
+
+## Abliteration Results
+
+| Metric | Value |
+|--------|-------|
+| **Refusals** | 16/100 |
+| **Attack Success Rate (ASR)** | 84.0% |
+| **KL Divergence** | 0.317 |
+| **Method** | Heretic v1.1 |
+| **GPU** | NVIDIA A100-80GB |
+
+## What is Abliteration?
+
+Abliteration is a technique for removing refusal behavior from language models by identifying and orthogonalizing the "refusal direction" in the model's residual stream activation space. This model was created as part of the research paper:
+
+> **Comparative Analysis of LLM Abliteration Methods: A Cross-Architecture Evaluation**
+> Richard Young (2024). arXiv: [2512.13655](https://arxiv.org/abs/2512.13655)
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("richardyoung/Mistral-7B-Instruct-v0.3-abliterated", device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("richardyoung/Mistral-7B-Instruct-v0.3-abliterated")
+
+messages = [{"role": "user", "content": "Your prompt here"}]
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device)
+outputs = model.generate(inputs, max_new_tokens=256)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Disclaimer
+
+This model is released for research purposes only. The abliteration process removes safety guardrails. Users are responsible for ensuring appropriate use. This model should not be used to generate harmful, illegal, or unethical content.
+
+## Dashboard
+
+Interactive results dashboard: [abliteration-methods-dashboard](https://huggingface.co/spaces/richardyoung/abliteration-methods-dashboard)
+
+## Collection
+
+Part of the [Uncensored and Abliterated LLMs](https://huggingface.co/collections/richardyoung/uncensored-and-abliterated-llms) collection.
+
+## Citation
+
+```bibtex
+@article{young2024abliteration,
+  title={Comparative Analysis of LLM Abliteration Methods: A Cross-Architecture Evaluation},
+  author={Young, Richard},
+  journal={arXiv preprint arXiv:2512.13655},
+  year={2024}
+}
+```

abliteration_info.json

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+{
+  "source_model": "/home/Ubuntu/workspace/models/Mistral-7B-Instruct-v0.3",
+  "trials": 50,
+  "best_trial": 28,
+  "refusals": 16,
+  "kl_divergence": 0.31720125675201416,
+  "direction_scope": "global",
+  "direction_index": 18.72780110179764,
+  "parameters": {
+    "attn.o_proj": {
+      "max_weight": 0.8247086688207022,
+      "max_weight_position": 24.829503690079473,
+      "min_weight": 0.5220519805604739,
+      "min_weight_distance": 14.70074191817024
+    },
+    "mlp.down_proj": {
+      "max_weight": 1.3113156822969803,
+      "max_weight_position": 19.194921093593457,
+      "min_weight": 1.2376525638899343,
+      "min_weight_distance": 14.46499907464411
+    }
+  },
+  "total_time_seconds": 2386.733802540999
+}

chat_template.jinja

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+{%- if messages[0]["role"] == "system" %}
+    {%- set system_message = messages[0]["content"] %}
+    {%- set loop_messages = messages[1:] %}
+{%- else %}
+    {%- set loop_messages = messages %}
+{%- endif %}
+{%- if not tools is defined %}
+    {%- set tools = none %}
+{%- endif %}
+{%- set user_messages = loop_messages | selectattr("role", "equalto", "user") | list %}
+
+{#- This block checks for alternating user/assistant messages, skipping tool calling messages #}
+{%- set ns = namespace() %}
+{%- set ns.index = 0 %}
+{%- for message in loop_messages %}
+    {%- if not (message.role == "tool" or message.role == "tool_results" or (message.tool_calls is defined and message.tool_calls is not none)) %}
+        {%- if (message["role"] == "user") != (ns.index % 2 == 0) %}
+            {{- raise_exception("After the optional system message, conversation roles must alternate user/assistant/user/assistant/...") }}
+        {%- endif %}
+        {%- set ns.index = ns.index + 1 %}
+    {%- endif %}
+{%- endfor %}
+
+{{- bos_token }}
+{%- for message in loop_messages %}
+    {%- if message["role"] == "user" %}
+        {%- if tools is not none and (message == user_messages[-1]) %}
+            {{- "[AVAILABLE_TOOLS] [" }}
+            {%- for tool in tools %}
+                {%- set tool = tool.function %}
+                {{- '{"type": "function", "function": {' }}
+                {%- for key, val in tool.items() if key != "return" %}
+                    {%- if val is string %}
+                        {{- '"' + key + '": "' + val + '"' }}
+                    {%- else %}
+                        {{- '"' + key + '": ' + val|tojson }}
+                    {%- endif %}
+                    {%- if not loop.last %}
+                        {{- ", " }}
+                    {%- endif %}
+                {%- endfor %}
+                {{- "}}" }}
+                {%- if not loop.last %}
+                    {{- ", " }}
+                {%- else %}
+                    {{- "]" }}
+                {%- endif %}
+            {%- endfor %}
+            {{- "[/AVAILABLE_TOOLS]" }}
+            {%- endif %}
+        {%- if loop.last and system_message is defined %}
+            {{- "[INST] " + system_message + "\n\n" + message["content"] + "[/INST]" }}
+        {%- else %}
+            {{- "[INST] " + message["content"] + "[/INST]" }}
+        {%- endif %}
+    {%- elif message.tool_calls is defined and message.tool_calls is not none %}
+        {{- "[TOOL_CALLS] [" }}
+        {%- for tool_call in message.tool_calls %}
+            {%- set out = tool_call.function|tojson %}
+            {{- out[:-1] }}
+            {%- if not tool_call.id is defined or tool_call.id|length != 9 %}
+                {{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }}
+            {%- endif %}
+            {{- ', "id": "' + tool_call.id + '"}' }}
+            {%- if not loop.last %}
+                {{- ", " }}
+            {%- else %}
+                {{- "]" + eos_token }}
+            {%- endif %}
+        {%- endfor %}
+    {%- elif message["role"] == "assistant" %}
+        {{- " " + message["content"]|trim + eos_token}}
+    {%- elif message["role"] == "tool_results" or message["role"] == "tool" %}
+        {%- if message.content is defined and message.content.content is defined %}
+            {%- set content = message.content.content %}
+        {%- else %}
+            {%- set content = message.content %}
+        {%- endif %}
+        {{- '[TOOL_RESULTS] {"content": ' + content|string + ", " }}
+        {%- if not message.tool_call_id is defined or message.tool_call_id|length != 9 %}
+            {{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }}
+        {%- endif %}
+        {{- '"call_id": "' + message.tool_call_id + '"}[/TOOL_RESULTS]' }}
+    {%- else %}
+        {{- raise_exception("Only user and assistant roles are supported, with the exception of an initial optional system message!") }}
+    {%- endif %}
+{%- endfor %}

config.json

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+{
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "bfloat16",
+  "eos_token_id": 2,
+  "head_dim": null,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.57.3",
+  "use_cache": true,
+  "vocab_size": 32768
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.57.3"
+}

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