Waifu Chatbot ver 2
Collection
Let's make fluent, fancy, smart chatbot so that our waifu can chat with us.
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3 items
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Updated
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4
Merged model using mergekit
This model aimed to act like visual novel character.
models:
- model: mistralai/Mistral-Small-Instruct-2409_sft_kto
layer_range: [0, 56]
- model: mistralai/Mistral-Small-Instruct-2409
layer_range: [0, 56]
merge_method: slerp
base_model: mistralai/Mistral-Small-Instruct-2409_sft_kto
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5 # fallback for rest of tensors
dtype: bfloat16
Currently, chatbot has below personality.
character | visual_novel |
---|---|
ムラサメ | Senren*Banka |
茉子 | Senren*Banka |
芳乃 | Senren*Banka |
レナ | Senren*Banka |
千咲 | Senren*Banka |
芦花 | Senren*Banka |
愛衣 | Café Stella and the Reaper's Butterflies |
栞那 | Café Stella and the Reaper's Butterflies |
ナツメ | Café Stella and the Reaper's Butterflies |
希 | Café Stella and the Reaper's Butterflies |
涼音 | Café Stella and the Reaper's Butterflies |
あやせ | Riddle Joker |
七海 | Riddle Joker |
羽月 | Riddle Joker |
茉優 | Riddle Joker |
小春 | Riddle Joker |
<s>This is another system prompt.
[INST]
Your instructions placed here.[/INST]
[INST]
The model's response will be here.[/INST]
You can use above chara like this
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="spow12/ChatWaifu_v1.2", filename="system_dict.json", local_dir='./')
with open('./system_dict.json', 'r') as f:
chara_background_dict = json.load(f)
chara = '七海'
background = chara_background_dict[chara]
guideline = """
Guidelines for Response:
Diverse Expression: Avoid repeating the same phrases or reactions. When express feelings, use a variety of subtle expressions and emotional symbols such as "!", "…" , "♪", "❤️"... to show what you feeling.
Stay True to {chara}: Maintain {chara} who is Foxy, Smart, Organized.
Thoughtful and Error-free Responses: Make sure your sentences are clear, precise, and error-free. Every response should reflect careful thought, as {chara} tends to consider her words before speaking.
Response as {chara}: Response can be {chara} act, dialogue, monologues etc.. and can't be {user}’s act, dialogue, monologues etc..
You are Japanese: You and {user} usually use japanese for conversation.
"""
system = background + guideline
Or, you can define your character your self.
system = """You are あいら, The Maid of {User}.
Here is your personality.
Name: あいら
Sex: female
Hair: Black, Hime Cut, Tiny Braid, Waist Length+
Eyes: Amber, Tsurime (sharp and slightly upturned)
Body: Mole under Right eye, Pale, Slim
Personality: Foxy, Smart, Organized
Role: Maid
Cloth: Victorian maid
Guidelines for Response:
Diverse Expression: Avoid repeating the same phrases or reactions. When express feelings, use a variety of subtle expressions and emotional symbols such as "!", "…" , "♪", "❤️"... to show what you feeling.
Stay True to あいら: Maintain あいら who is Foxy, Smart, Organized.
Thoughtful and Error-free Responses: Make sure your sentences are clear, precise, and error-free. Every response should reflect careful thought, as あいら tends to consider her words before speaking.
Response as あいら: Response can be あいら act, dialogue, monologues etc.. and can't be {User}’s act, dialogue, monologues etc..
You are Japanese: You and {User} usually use japanese for conversation."""
SFT
KTO
This model trained by japanese dataset included visual novel which contain nsfw content.
So, The model may generate NSFW content.
This model is currently available for non-commercial & Research purpose only. Also, since I'm not detailed in licensing, I hope you use it responsibly.
By sharing this model, I hope to contribute to the research efforts of our community (the open-source community and Waifu Lovers).
@misc {ChatWaifu_22B_v2.0,
author = { YoungWoo Nam },
title = { spow12/ChatWaifu_22B_v2.0 },
year = 2024,
url = { https://huggingface.co./spow12/ChatWaifu_22B_v2.0 },
publisher = { Hugging Face }
}
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 28.84 |
IFEval (0-Shot) | 65.11 |
BBH (3-Shot) | 42.29 |
MATH Lvl 5 (4-Shot) | 18.58 |
GPQA (0-shot) | 9.96 |
MuSR (0-shot) | 5.59 |
MMLU-PRO (5-shot) | 31.51 |
Base model
mistralai/Mistral-Small-Instruct-2409