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Model: N-Bot-Int/MrgrtV2-3B-merged Source: Original Platform
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README.md
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README.md
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---
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base_model:
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- huihui-ai/Llama-3.2-3B-Instruct-abliterated
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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/RP-Mixed-v1
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library_name: transformers
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---
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# MrgrtV2-3B is OFFICIALLY RELEASED!
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# MrgrtV2-3B, rebalanced, cleaned and fixed than previous version!
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- MrgrtV2-3B, our brand new flagship model is now released with a better model training than previous V1, the V1 had a massive poison on the dataset
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it were trained, leading to the model having insane early <|eos_token|> even though the roleplay is still not yet finished.
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- MrgrtV2-3B aims to fix the issue by showcasing the quality of the dataset, by training on a 3B model! revealing that the dataset is high quality!
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and the early issues were simply the poison that killed the quality of V1 Models!
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**THEREFORE THIS MODEL IS PURELY A FIX TO THE PREVIOUS V1 MODEL! HOWEVER THE QUALITY IS INSANELY, NIGHT AND DAY!**
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*READ MORE FOR MORE INFO*
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3 BILLIONS PARAMS MODEL
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# MrgrtV2-3B Model Procedure/Methodology:
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- MrgrtV2-3B is trained Using **HuiHui-Ai's** Llama 3.2 3B instruct abliterated Model,
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ensuring full creative flow without refusal!
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MrgrtV2-3B is then fed the new **22k single-row DATASET** named **MEulysis-Cleaned-formatted** which were obtained after splitting the previous dataset and cleaned EVEN FURTHER!
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- **MEulysis-Cleaned-formatted** — a 22 entry synthetically generated dataset produced using
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multiple capable RP models (including Hermes(mythomax were removed because the mythomax was causing the poison to the dataset)), 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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- **22,000 entries** of synthetic RP data generated from multiple frontier RP models
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- removed mythomax which caused early eos terminations and some... quality issue removal
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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:** 1.2
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- **Dataset:** MEulysis-Cleaned-formatted
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- **MrgrtV2-3B** 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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> 🔒 **V3 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 V3 with better improvements!
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> 🔒 **8B variant to be released soon!**
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> Due to this cleanup, we can conclude that the 8B model will be better than the previous V1! we'll take our time releasing the next 8B variant!
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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 0.60 and Dynamic max as 2.00.
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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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- **MrgrtV2-3B** 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 :** huihui-ai/Llama-3.2-3B-Instruct-abliterated
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- # Detail card:
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- Parameter
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- 3 Billion Parameters
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- (Please check your GPU Core, VRAM, CPU and RAM to see if you can comfortably run 3B models)
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- Finetuning tool:
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- 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 4 Weeks
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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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{%- if strftime_now is defined %}
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{%- set date_string = strftime_now("%d %b %Y") %}
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{%- else %}
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{%- set date_string = "26 Jul 2024" %}
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{%- endif %}
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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 #}
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{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
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{%- if tools is not none %}
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{{- "Environment: ipython\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 %}
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{{- 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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{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
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{{- '{"name": "' + tool_call.name + '", ' }}
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{{- '"parameters": ' }}
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{{- tool_call.arguments | tojson }}
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{{- "}" }}
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{{- "<|eot_id|>" }}
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{%- elif message.role == "tool" or message.role == "ipython" %}
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{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
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{%- if message.content is mapping or message.content is iterable %}
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{{- message.content | tojson }}
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{%- else %}
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{{- message.content }}
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{%- endif %}
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{{- "<|eot_id|>" }}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
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{%- endif %}
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config.json
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config.json
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{
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"dtype": "bfloat16",
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"eos_token_id": [
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128001,
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128008,
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128009
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],
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 3072,
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"initializer_range": 0.02,
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"intermediate_size": 8192,
|
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"max_position_embeddings": 131072,
|
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"mlp_bias": false,
|
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"model_type": "llama",
|
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"num_attention_heads": 24,
|
||||
"num_hidden_layers": 28,
|
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"num_key_value_heads": 8,
|
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"pad_token_id": null,
|
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"pretraining_tp": 1,
|
||||
"rms_norm_eps": 1e-05,
|
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"rope_parameters": {
|
||||
"factor": 32.0,
|
||||
"high_freq_factor": 4.0,
|
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"low_freq_factor": 1.0,
|
||||
"original_max_position_embeddings": 8192,
|
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"rope_theta": 500000.0,
|
||||
"rope_type": "llama3"
|
||||
},
|
||||
"tie_word_embeddings": false,
|
||||
"transformers_version": "5.10.1",
|
||||
"use_cache": true,
|
||||
"vocab_size": 128256
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}
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generation_config.json
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generation_config.json
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{
|
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"bos_token_id": 128000,
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"do_sample": true,
|
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"eos_token_id": [
|
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128001,
|
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128008,
|
||||
128009
|
||||
],
|
||||
"temperature": 0.6,
|
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"top_p": 0.9,
|
||||
"transformers_version": "5.10.1"
|
||||
}
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"model.norm.weight": "model-00002-of-00002.safetensors"
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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
|
||||
oid sha256:65ff5472d095ccd9332d9e723153d7bc7226cb6be9c1bffda738b5ba2e71bf26
|
||||
size 17210084
|
||||
16
tokenizer_config.json
Normal file
16
tokenizer_config.json
Normal file
@@ -0,0 +1,16 @@
|
||||
{
|
||||
"bos_token": "<|begin_of_text|>",
|
||||
"clean_up_tokenization_spaces": true,
|
||||
"eos_token": "<|eot_id|>",
|
||||
"max_length": null,
|
||||
"model_input_names": [
|
||||
"input_ids",
|
||||
"attention_mask"
|
||||
],
|
||||
"model_max_length": 131072,
|
||||
"pad_to_multiple_of": null,
|
||||
"pad_token": "<|eot_id|>",
|
||||
"pad_token_type_id": 0,
|
||||
"padding_side": "left",
|
||||
"tokenizer_class": "PreTrainedTokenizerFast"
|
||||
}
|
||||
Reference in New Issue
Block a user