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Model: 0xA50C1A1/Mistral-Nemo-Instruct-2407-Heretic-v2 Source: Original Platform
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README.md
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---
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language:
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- en
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base_model:
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- unsloth/Mistral-Nemo-Instruct-2407
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library_name: transformers
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license: apache-2.0
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tags:
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- mistral
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- unsloth
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- transformers
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- heretic
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- uncensored
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- decensored
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- abliterated
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---
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# 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
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## Abliteration parameters
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| Parameter | Value |
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| :-------- | :---: |
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| **direction_index** | 18.46 |
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| **attn.o_proj.max_weight** | 1.29 |
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| **attn.o_proj.max_weight_position** | 29.40 |
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| **attn.o_proj.min_weight** | 1.08 |
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| **attn.o_proj.min_weight_distance** | 18.39 |
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| **mlp.down_proj.max_weight** | 1.47 |
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| **mlp.down_proj.max_weight_position** | 24.17 |
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| **mlp.down_proj.min_weight** | 1.41 |
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| **mlp.down_proj.min_weight_distance** | 19.35 |
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## Performance
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| Metric | This model | Original model ([unsloth/Mistral-Nemo-Instruct-2407](https://huggingface.co/unsloth/Mistral-Nemo-Instruct-2407)) |
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| :----- | :--------: | :---------------------------: |
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| **KL divergence** | 0.0574 | 0 *(by definition)* |
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| **Refusals** | 4/100 | 88/100 |
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-----
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# Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!
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We have a free Google Colab Tesla T4 notebook for Mistral Nemo 12b here: https://colab.research.google.com/drive/17d3U-CAIwzmbDRqbZ9NnpHxCkmXB6LZ0?usp=sharing
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/>](https://discord.gg/u54VK8m8tk)
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/buy%20me%20a%20coffee%20button.png" width="200"/>](https://ko-fi.com/unsloth)
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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## ✨ Finetune for Free
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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.
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| Unsloth supports | Free Notebooks | Performance | Memory use |
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|-----------------|--------------------------------------------------------------------------------------------------------------------------|-------------|----------|
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| **Llama-3 8b** | [▶️ Start on Colab](https://colab.research.google.com/drive/135ced7oHytdxu3N2DNe1Z0kqjyYIkDXp?usp=sharing) | 2.4x faster | 58% less |
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| **Gemma 7b** | [▶️ Start on Colab](https://colab.research.google.com/drive/10NbwlsRChbma1v55m8LAPYG15uQv6HLo?usp=sharing) | 2.4x faster | 58% less |
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| **Mistral 7b** | [▶️ Start on Colab](https://colab.research.google.com/drive/1Dyauq4kTZoLewQ1cApceUQVNcnnNTzg_?usp=sharing) | 2.2x faster | 62% less |
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| **Llama-2 7b** | [▶️ Start on Colab](https://colab.research.google.com/drive/1lBzz5KeZJKXjvivbYvmGarix9Ao6Wxe5?usp=sharing) | 2.2x faster | 43% less |
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| **TinyLlama** | [▶️ Start on Colab](https://colab.research.google.com/drive/1AZghoNBQaMDgWJpi4RbffGM1h6raLUj9?usp=sharing) | 3.9x faster | 74% less |
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| **CodeLlama 34b** A100 | [▶️ Start on Colab](https://colab.research.google.com/drive/1y7A0AxE3y8gdj4AVkl2aZX47Xu3P1wJT?usp=sharing) | 1.9x faster | 27% less |
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| **Mistral 7b** 1xT4 | [▶️ Start on Kaggle](https://www.kaggle.com/code/danielhanchen/kaggle-mistral-7b-unsloth-notebook) | 5x faster\* | 62% less |
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| **DPO - Zephyr** | [▶️ Start on Colab](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing) | 1.9x faster | 19% less |
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- This [conversational notebook](https://colab.research.google.com/drive/1Aau3lgPzeZKQ-98h69CCu1UJcvIBLmy2?usp=sharing) is useful for ShareGPT ChatML / Vicuna templates.
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- 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.
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- \* Kaggle has 2x T4s, but we use 1. Due to overhead, 1x T4 is 5x faster.
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chat_template.jinja
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{%- if messages[0]["role"] == "system" %}
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{%- set system_message = messages[0]["content"] %}
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{%- set loop_messages = messages[1:] %}
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{%- else %}
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{%- set loop_messages = messages %}
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{%- endif %}
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{%- if not tools is defined %}
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{%- set tools = none %}
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{%- endif %}
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{%- set user_messages = loop_messages | selectattr("role", "equalto", "user") | list %}
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{#- This block checks for alternating user/assistant messages, skipping tool calling messages #}
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{%- set ns = namespace() %}
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{%- set ns.index = 0 %}
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{%- for message in loop_messages %}
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{%- if not (message.role == "tool" or message.role == "tool_results" or (message.tool_calls is defined and message.tool_calls is not none)) %}
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{%- if (message["role"] == "user") != (ns.index % 2 == 0) %}
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{{- raise_exception("After the optional system message, conversation roles must alternate user/assistant/user/assistant/...") }}
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{%- endif %}
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{%- set ns.index = ns.index + 1 %}
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{%- endif %}
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{%- endfor %}
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{{- bos_token }}
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{%- for message in loop_messages %}
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{%- if message["role"] == "user" %}
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{%- if tools is not none and (message == user_messages[-1]) %}
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{{- "[AVAILABLE_TOOLS][" }}
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{%- for tool in tools %}
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{%- set tool = tool.function %}
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{{- '{"type": "function", "function": {' }}
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{%- for key, val in tool.items() if key != "return" %}
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{%- if val is string %}
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{{- '"' + key + '": "' + val + '"' }}
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{%- else %}
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{{- '"' + key + '": ' + val|tojson }}
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{%- endif %}
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{%- if not loop.last %}
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{{- ", " }}
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{%- endif %}
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{%- endfor %}
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{{- "}}" }}
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{%- if not loop.last %}
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{{- ", " }}
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{%- else %}
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{{- "]" }}
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{%- endif %}
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{%- endfor %}
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{{- "[/AVAILABLE_TOOLS]" }}
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{%- endif %}
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{%- if loop.last and system_message is defined %}
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{{- "[INST]" + system_message + "\n\n" + message["content"] + "[/INST]" }}
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{%- else %}
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{{- "[INST]" + message["content"] + "[/INST]" }}
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{%- endif %}
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{%- elif (message.tool_calls is defined and message.tool_calls is not none) %}
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{% generation %}
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{{- "[TOOL_CALLS][" }}
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{%- for tool_call in message.tool_calls %}
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{%- set out = tool_call.function|tojson %}
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{{- out[:-1] }}
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{%- if not tool_call.id is defined or tool_call.id|length != 9 %}
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{{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }}
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{%- endif %}
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{{- ', "id": "' + tool_call.id + '"}' }}
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{%- if not loop.last %}
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{{- ", " }}
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{%- else %}
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{{- "]" + eos_token }}
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{%- endif %}
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{%- endfor %}
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{% endgeneration %}
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{%- elif message["role"] == "assistant" %}
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{% generation %}
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{{- message["content"] + eos_token }}
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{% endgeneration %}
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{%- elif message["role"] == "tool_results" or message["role"] == "tool" %}
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{%- if message.content is defined and message.content.content is defined %}
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{%- set content = message.content.content %}
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{%- else %}
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{%- set content = message.content %}
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{%- endif %}
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{{- '[TOOL_RESULTS]{"content": ' + content|string + ", " }}
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{%- if not message.tool_call_id is defined or message.tool_call_id|length != 9 %}
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{{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }}
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{%- endif %}
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{{- '"call_id": "' + message.tool_call_id + '"}[/TOOL_RESULTS]' }}
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{%- else %}
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{{- raise_exception("Only user and assistant roles are supported, with the exception of an initial optional system message!") }}
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{%- endif %}
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{%- endfor %}
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config.json
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{
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"dtype": "bfloat16",
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"eos_token_id": 2,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 131072,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 40,
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"num_key_value_heads": 8,
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"pad_token_id": 10,
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"rms_norm_eps": 1e-05,
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"rope_parameters": {
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"rope_theta": 1000000.0,
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"rope_type": "default"
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},
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"sliding_window": null,
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"tie_word_embeddings": false,
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"transformers_version": "5.3.0",
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"unsloth_fixed": true,
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"use_cache": true,
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"vocab_size": 131072
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"max_length": 131072,
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"pad_token_id": 10,
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"transformers_version": "5.3.0"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:367fbe8ecd01f267811717f26f3a5912311425eeaa173ab25728a273c2e8f883
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size 24495607560
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tokenizer.json
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:8bf3b3d6214dce22c2aa088e17fd3d059bb7069b0b1c8098ace2867d4b96b20a
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size 17078447
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