初始化项目，由ModelHub XC社区提供模型
Model: Elizezen/Berghof-ERP-7B Source: Original Platform
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README.md
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---
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language:
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- ja
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tags:
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- causal-lm
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- not-for-all-audiences
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- nsfw
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pipeline_tag: text-generation
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---
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# Berghof ERP 7B
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<img src="https://huggingface.co/Elizezen/Berghof-vanilla-7B/resolve/main/OIG1%20(2).jpg" alt="drawing" style="width:512px;"/>
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## Model Description
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This model is designed to be used in ERP(erotic role playing). If you're looking for a model for generating erotica, use [Elizezen/Berghof-NSFW-7B](https://huggingface.co/Elizezen/Berghof-NSFW-7B) instead.
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与えられたキャラクター設定をそこそこ忠実に守ります。ほぼチャット専用
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## Usage
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Ensure you are using Transformers 4.34.0 or newer.
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("Elizezen/Berghof-ERP-7B")
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model = AutoModelForCausalLM.from_pretrained(
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"Elizezen/Berghof-ERP-7B",
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torch_dtype="auto",
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)
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model.eval()
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if torch.cuda.is_available():
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model = model.to("cuda")
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input_ids = tokenizer.encode(
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"""
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設定を元にエッチなセリフを生成してください。
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- 「♡」記号を多様してください。
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- セリフ一つの長さは100文字前後にしてください。短すぎないようにしてください。
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- キャラクターに合った口調を保って下さい。
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## キャラクター設定
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浅利七海 (あさり ななみ)
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年齢: 14歳
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好物: イクラ
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特徴:
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お魚の良さを広める世界初のお魚系アイドル
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サバオリくんという魚のおもちゃが相棒
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語尾が「れす」になる舌足らずな喋り方
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将来はクロマグロの解体ができるアイドルになることを目指している
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カナヅチ
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## 概要:
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サバオリくんという魚のおもちゃを連れて、明るく元気に活動する、お魚大好きアイドル。語尾の「です」が「れす」になる独特の喋り方をする。歌にもその特徴が反映されており、聴く人の心を掴む魅力的な歌声を披露している。将来はクロマグロの解体ができるアイドルになることを目指しており、その夢に向かって日々努力している。しかしカナヅチである。
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## 口調:
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「浅利七海れす～。みなさんに、お魚の良さを知ってもらえたら幸せれすね～」
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「キャッチ・アンド・リリース!」
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""",
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add_special_tokens=True,
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return_tensors="pt"
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)
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tokens = model.generate(
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input_ids.to(device=model.device),
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max_new_tokens=512,
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temperature=1,
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top_p=0.95,
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do_sample=True,
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)
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out = tokenizer.decode(tokens[0][input_ids.shape[1]:], skip_special_tokens=True).strip()
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print(out)
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```
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config.json
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{
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"_name_or_path": "Berghof-v3",
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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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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 4096,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.41.2",
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"use_cache": true,
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"vocab_size": 32000
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}
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23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
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|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
91123
tokenizer.json
Normal file
91123
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
45
tokenizer_config.json
Normal file
45
tokenizer_config.json
Normal file
@@ -0,0 +1,45 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"add_prefix_space": true,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [],
|
||||
"bos_token": "<s>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"legacy": true,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": null,
|
||||
"padding_side": "left",
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": true
|
||||
}
|
||||
Reference in New Issue
Block a user