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Model: N-Bot-Int/MrgrtV1-8B-merged Source: Original Platform
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README.md
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---
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base_model:
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- MuXodious/Llama-3.3-8B-Instruct-128K-PaperWitch-heresy
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- llama
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- Uncensored
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- trl
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- roleplay
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- conversational
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license: agpl-3.0
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language:
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- en
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pipeline_tag: text-generation
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datasets:
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- N-Bot-Int/Iris-Uncensored-Reformat-R2
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- N-Bot-Int/RP-Mixed-v1
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library_name: transformers
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---
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# MrgrtV1-8B is OFFICIALLY RELEASED!
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# MrgrtV1-8B for Better Roleplaying with Maximum Quality improvements!
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- MrgrtV1-8B *(pronounecd Margaret-V1)* is our brand new **AI MODEL** built on top of **MuXodious/Llama-3.3-8B-Instruct-128K-PaperWitch-heresy**,
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MrgrtV1-8B is one of our Checkpoint we want to share to you, to showcase the current **Improvement** of our new training pipeline and
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New **Innovations**.
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- MrgrtV1-8B Is Our **NEWEST** model, trained on kaggle for **2 Weeks**, which showcases the most **COHERENCE** compared to other models we made!
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MrgrtV1-8B excels greatly with Roleplay Focused, however **DUE TO OUR LACK OF COMPLETE OPEN DATA**, the ai model might produce subpar quality to Open Roleplay
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Compared to Contained-Roleplay focused scenarios!
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- MrgrtV1-8B is trained on our **IMPROVED MEulysis** dataset, that aims to dethrone **Misthena** and our previous **OpenElla-NovelWriter** Models!
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*READ MORE FOR MORE INFO*
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8 BILLIONS PARAMS MODEL
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# MrgrtV1-8B Model Procedure/Methodology:
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- MrgrtV1-8B is trained Using **MuXodious**'s Llama-3.3-8B Paperwitch Version[Thank you SO MUCH for all the help @redaihf, @MuXodious and @Naphula](https://huggingface.co/N-Bot-Int/OpenElla-NovelWriter-8B-V2-merged/discussions/1) of the Model,
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ensuring full creative flow without refusal!
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MrgrtV1-8B is then fed the new **100K single-row DATASET** named **MEulysis-Cleaned** which were obtained after splitting the previous dataset and cleaned!
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- **MEulysis-Cleaned** — a 100k entry synthetically generated dataset produced using
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multiple capable RP models (including Mythomax and Hermes), then carefully cleaned,
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formatted with Llama 3 chat formatting, and then, tuned across a wide range of roleplay scenarios.
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### What makes MEulysis-Cleaned different?
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- **100,000 entries** of synthetic RP data generated from multiple frontier RP models
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- Wide RP focus covering diverse character types, settings, and narrative styles
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- Includes **MOST ELABORATE EXPERIENCES** to **MOST TABOO SCENARIOS**
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- Clear formatting guidance baked into the data — proper use of `"dialogue"` and `*actions*`
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- Now includes **Llama 3 chat** formatting to maximize quality on Llama models we'll release!
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- Fully cleaned and curated for quality and consistency
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# Training Details
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- **Finetuning Tool:** Unsloth AI + Huggingface TRL(we uses our brand new **Kaggle Extenderizer** to extend training without starting from scratch)
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- **Training Platform:** Kaggle Free Tier with T4 x2!
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- **Epochs:** 3
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- **Final Training Loss:** 1.1
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- **Dataset:** MEulysis-Cleaned
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- **MrgrtV1-8B** is Our Brand New Powerful Model, If you ever encountered any issue, Want to commission us, or have any suggestions, please email us directly through
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[nexus.networkinteractives@gmail.com](mailto:nexus.networkinteractives@gmail.com)
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we value any reports, suggestions to how we improve future Model,
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Once again feel free to finetune the model to your likings, However please consider Adding this Page
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for **CREDITS**
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- Please handle the AI with Care and ethical considerations, when **FINETUNING** this AI model, due to its **UNCENSORED** Nature.
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- We are not responsible for what this model generates. Use it responsibly and legally. You downloaded it, you own what you do with it.
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---
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# What's Coming Next?
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> 🔒 **V2 will released with better support for more OPEN ROLEPLAY SCENARIOS**
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> Right now the ai model is somewhat bad with Open roleplay, however we'll do our best to release the V2 with better improvements!
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> 🔒 **4b variant to be released soon!**
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> 4B variants trained on the same dataset, with same training methodology will be released shortly for those who lack system resources however still wish to use
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> High Quality RPing model!
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> 🔒 **1B variant to be released**
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> Experimental 1B variant with the same training methodology will be released following 4B, this is **EXTREMELY EXPERIMENTAL**, 1B are not good for Roleplaying
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> however we share them nonetheless!
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> 🔒 **Release PEFT Soon**
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> New PEFT releases of the model, will now be released late. Supporters on our Ko-fi can however request for the PEFT(through gmail) if they ever want to!
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> (This is to thank our Ko-fi supporters!)
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[](https://ko-fi.com/J3J61D8NHV)
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> Benchmarks are also in the pipeline and will be added once available.
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---
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# Notices & Usage Tips
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- **Use Llama 3 format** — the model is based on Llama 3, Soooooo using Llama 3 works best!.
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- **Calibrate per character card** — every character is different, adjust your prompt, Model's settings(ie, temps, Top-K etc.) accordingly. However
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We recommend(if you're using koboldcpp), to use DynaTemp with Dynamic Min as 0.50 and Dynamic max as 1.50.
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That's the setting we found to make the model more coherent, less hallucination whilst making the model adventurous!
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---
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# About
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- **MrgrtV1-8B** is
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- **Developed by:** N-Bot-Int
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- **License:** agpl 3.0
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- **Finetuned from model :** MuXodious/Llama-3.3-8B-Instruct-128K-PaperWitch-heresy
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- # Detail card:
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- Parameter
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||||
- 8 Billion Parameters
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||||
- (Please check your GPU Core, VRAM, CPU and RAM to see if you can comfortably run 8B models)
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|
||||
- Finetuning tool:
|
||||
- Unsloth AI
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- This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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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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- Fine-tuned Using:
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- Kaggle Free Tier with T4 x2 for 2 Weeks
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105
chat_template.jinja
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chat_template.jinja
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{{- bos_token }}
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{%- if custom_tools is defined %}
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{%- set tools = custom_tools %}
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{%- endif %}
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{%- if not tools_in_user_message is defined %}
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{%- set tools_in_user_message = true %}
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{%- endif %}
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{%- if not date_string is defined %}
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{%- set date_string = "30 Dec 2025" %}
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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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{#- This block extracts the system message, so we can slot it into the right place. #}
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{%- if messages[0]['role'] == 'system' %}
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{%- set system_message = messages[0]['content']|trim %}
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{%- set messages = messages[1:] %}
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{%- else %}
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{%- set system_message = "" %}
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{%- endif %}
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{#- System message + builtin tools #}
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{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
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{%- if builtin_tools is defined or tools is not none %}
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{{- "Environment: ipython\n" }}
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{%- endif %}
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{%- if builtin_tools is defined %}
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{{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
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{%- endif %}
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{{- "Cutting Knowledge Date: December 2023\n" }}
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{{- "Today Date: " + date_string + "\n\n" }}
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{%- if tools is not none and not tools_in_user_message %}
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{{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
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{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
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{{- "Do not use variables.\n\n" }}
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{%- for t in tools %}
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{{- t | tojson(indent=4) }}
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{{- "\n\n" }}
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{%- endfor %}
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{%- endif %}
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{{- system_message }}
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{{- "<|eot_id|>" }}
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{#- Custom tools are passed in a user message with some extra guidance #}
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{%- if tools_in_user_message and not tools is none %}
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{#- Extract the first user message so we can plug it in here #}
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{%- if messages | length != 0 %}
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{%- set first_user_message = messages[0]['content']|trim %}
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{%- set messages = messages[1:] %}
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{%- else %}
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{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
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{%- endif %}
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{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
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{{- "Given the following functions, please respond with a JSON for a function call " }}
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{{- "with its proper arguments that best answers the given prompt.\n\n" }}
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||||
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
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||||
{{- "Do not use variables.\n\n" }}
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||||
{%- for t in tools %}
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{{- t | tojson(indent=4) }}
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{{- "\n\n" }}
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{%- endfor %}
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{{- first_user_message + "<|eot_id|>"}}
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{%- endif %}
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{%- for message in messages %}
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{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
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{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
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{%- elif 'tool_calls' in message %}
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{%- if not message.tool_calls|length == 1 %}
|
||||
{{- raise_exception("This model only supports single tool-calls at once!") }}
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{%- endif %}
|
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{%- set tool_call = message.tool_calls[0].function %}
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{%- if builtin_tools is defined and tool_call.name in builtin_tools %}
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||||
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
|
||||
{{- "<|python_tag|>" + tool_call.name + ".call(" }}
|
||||
{%- for arg_name, arg_val in tool_call.arguments | items %}
|
||||
{{- arg_name + '="' + arg_val + '"' }}
|
||||
{%- if not loop.last %}
|
||||
{{- ", " }}
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||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{{- ")" }}
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||||
{%- else %}
|
||||
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
|
||||
{{- '{"name": "' + tool_call.name + '", ' }}
|
||||
{{- '"parameters": ' }}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{{- "}" }}
|
||||
{%- endif %}
|
||||
{%- if builtin_tools is defined %}
|
||||
{#- This means we're in ipython mode #}
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||||
{{- "<|eom_id|>" }}
|
||||
{%- else %}
|
||||
{{- "<|eot_id|>" }}
|
||||
{%- endif %}
|
||||
{%- elif message.role == "tool" or message.role == "ipython" %}
|
||||
{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
|
||||
{%- if message.content is mapping or message.content is iterable %}
|
||||
{{- message.content | tojson }}
|
||||
{%- else %}
|
||||
{{- message.content }}
|
||||
{%- endif %}
|
||||
{{- "<|eot_id|>" }}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
|
||||
{%- endif %}
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36
config.json
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config.json
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{
|
||||
"architectures": [
|
||||
"LlamaForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 128000,
|
||||
"dtype": "bfloat16",
|
||||
"eos_token_id": 128009,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 4096,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 14336,
|
||||
"max_position_embeddings": 131072,
|
||||
"mlp_bias": false,
|
||||
"model_type": "llama",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 32,
|
||||
"num_key_value_heads": 8,
|
||||
"pad_token_id": null,
|
||||
"pretraining_tp": 1,
|
||||
"rms_norm_eps": 1e-05,
|
||||
"rope_parameters": {
|
||||
"factor": 8.0,
|
||||
"high_freq_factor": 4.0,
|
||||
"low_freq_factor": 1.0,
|
||||
"original_max_position_embeddings": 8192,
|
||||
"rope_theta": 500000.0,
|
||||
"rope_type": "llama3"
|
||||
},
|
||||
"tie_word_embeddings": false,
|
||||
"transformers_version": "5.8.1",
|
||||
"use_cache": true,
|
||||
"vocab_size": 128256
|
||||
}
|
||||
13
generation_config.json
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generation_config.json
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|
||||
{
|
||||
"bos_token_id": 128000,
|
||||
"do_sample": true,
|
||||
"eos_token_id": [
|
||||
128001,
|
||||
128008,
|
||||
128009
|
||||
],
|
||||
"max_length": 131072,
|
||||
"temperature": 0.6,
|
||||
"top_p": 0.9,
|
||||
"transformers_version": "5.8.1"
|
||||
}
|
||||
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3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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oid sha256:3c5cf44023714fb39b05e71e425f8d7b92805ff73f7988b083b8c87f0bf87393
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size 17209961
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15
tokenizer_config.json
Normal file
15
tokenizer_config.json
Normal file
@@ -0,0 +1,15 @@
|
||||
{
|
||||
"backend": "tokenizers",
|
||||
"bos_token": "<|begin_of_text|>",
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"pad_token": "<|eot_id|>",
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||||
"tokenizer_class": "TokenizersBackend"
|
||||
}
|
||||
Reference in New Issue
Block a user