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Model: 0xA50C1A1/Mistral-Nemo-Instruct-2407-Heretic-v2
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---
language:
- en
base_model:
- unsloth/Mistral-Nemo-Instruct-2407
library_name: transformers
license: apache-2.0
tags:
- mistral
- unsloth
- transformers
- heretic
- uncensored
- decensored
- abliterated
---
# This is a decensored version of [unsloth/Mistral-Nemo-Instruct-2407](https://huggingface.co/unsloth/Mistral-Nemo-Instruct-2407), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | 18.46 |
| **attn.o_proj.max_weight** | 1.29 |
| **attn.o_proj.max_weight_position** | 29.40 |
| **attn.o_proj.min_weight** | 1.08 |
| **attn.o_proj.min_weight_distance** | 18.39 |
| **mlp.down_proj.max_weight** | 1.47 |
| **mlp.down_proj.max_weight_position** | 24.17 |
| **mlp.down_proj.min_weight** | 1.41 |
| **mlp.down_proj.min_weight_distance** | 19.35 |
## Performance
| Metric | This model | Original model ([unsloth/Mistral-Nemo-Instruct-2407](https://huggingface.co/unsloth/Mistral-Nemo-Instruct-2407)) |
| :----- | :--------: | :---------------------------: |
| **KL divergence** | 0.0574 | 0 *(by definition)* |
| **Refusals** | 4/100 | 88/100 |
-----
# Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!
We have a free Google Colab Tesla T4 notebook for Mistral Nemo 12b here: https://colab.research.google.com/drive/17d3U-CAIwzmbDRqbZ9NnpHxCkmXB6LZ0?usp=sharing
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/>](https://discord.gg/u54VK8m8tk)
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/buy%20me%20a%20coffee%20button.png" width="200"/>](https://ko-fi.com/unsloth)
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
## ✨ Finetune for Free
All notebooks are **beginner friendly**! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model which can be exported to GGUF, vLLM or uploaded to Hugging Face.
| Unsloth supports | Free Notebooks | Performance | Memory use |
|-----------------|--------------------------------------------------------------------------------------------------------------------------|-------------|----------|
| **Llama-3 8b** | [▶️ Start on Colab](https://colab.research.google.com/drive/135ced7oHytdxu3N2DNe1Z0kqjyYIkDXp?usp=sharing) | 2.4x faster | 58% less |
| **Gemma 7b** | [▶️ Start on Colab](https://colab.research.google.com/drive/10NbwlsRChbma1v55m8LAPYG15uQv6HLo?usp=sharing) | 2.4x faster | 58% less |
| **Mistral 7b** | [▶️ Start on Colab](https://colab.research.google.com/drive/1Dyauq4kTZoLewQ1cApceUQVNcnnNTzg_?usp=sharing) | 2.2x faster | 62% less |
| **Llama-2 7b** | [▶️ Start on Colab](https://colab.research.google.com/drive/1lBzz5KeZJKXjvivbYvmGarix9Ao6Wxe5?usp=sharing) | 2.2x faster | 43% less |
| **TinyLlama** | [▶️ Start on Colab](https://colab.research.google.com/drive/1AZghoNBQaMDgWJpi4RbffGM1h6raLUj9?usp=sharing) | 3.9x faster | 74% less |
| **CodeLlama 34b** A100 | [▶️ Start on Colab](https://colab.research.google.com/drive/1y7A0AxE3y8gdj4AVkl2aZX47Xu3P1wJT?usp=sharing) | 1.9x faster | 27% less |
| **Mistral 7b** 1xT4 | [▶️ Start on Kaggle](https://www.kaggle.com/code/danielhanchen/kaggle-mistral-7b-unsloth-notebook) | 5x faster\* | 62% less |
| **DPO - Zephyr** | [▶️ Start on Colab](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing) | 1.9x faster | 19% less |
- This [conversational notebook](https://colab.research.google.com/drive/1Aau3lgPzeZKQ-98h69CCu1UJcvIBLmy2?usp=sharing) is useful for ShareGPT ChatML / Vicuna templates.
- This [text completion notebook](https://colab.research.google.com/drive/1ef-tab5bhkvWmBOObepl1WgJvfvSzn5Q?usp=sharing) is for raw text. This [DPO notebook](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing) replicates Zephyr.
- \* Kaggle has 2x T4s, but we use 1. Due to overhead, 1x T4 is 5x faster.

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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) %}
{% generation %}
{{- "[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 %}
{% endgeneration %}
{%- elif message["role"] == "assistant" %}
{% generation %}
{{- message["content"] + eos_token }}
{% endgeneration %}
{%- 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 %}

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{
"architectures": [
"MistralForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 1,
"dtype": "bfloat16",
"eos_token_id": 2,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 5120,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 131072,
"model_type": "mistral",
"num_attention_heads": 32,
"num_hidden_layers": 40,
"num_key_value_heads": 8,
"pad_token_id": 10,
"rms_norm_eps": 1e-05,
"rope_parameters": {
"rope_theta": 1000000.0,
"rope_type": "default"
},
"sliding_window": null,
"tie_word_embeddings": false,
"transformers_version": "5.3.0",
"unsloth_fixed": true,
"use_cache": true,
"vocab_size": 131072
}

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{
"_from_model_config": true,
"bos_token_id": 1,
"eos_token_id": 2,
"max_length": 131072,
"pad_token_id": 10,
"transformers_version": "5.3.0"
}

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