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Model: roleplay/Peach-9B-8k-Roleplay
Source: Original Platform

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PeachGirl.png

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README.md

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+---
+license: mit
+language:
+- zh
+- en
+pipeline_tag: text-generation
+tags:
+- roleplay
+- rp
+- character
+---
+
+<!-- header start -->
+<!-- 200823 -->
+<div style="width: auto; margin-left: auto; margin-right: auto">
+<img src="./PeachGirl.png" alt="Peach" style="width: 100%; min-width: 400px; display: block; margin: auto;">
+</div>
+<!-- header end -->
+
+# Peach-9B-8k-Roleplay
+
+Peach-9B-8k-Roleplay is a chat large language model obtained by finetuning [01-ai/Yi-1.5-9B](https://huggingface.co/01-ai/Yi-1.5-9B) model on more than 100K conversations created through our data synthesis approach. 
+
+**Maybe The Best LLM with Small Parameters under 34B**
+
+## How to start
+The version of Transformers we are using is as follows, but a newer version may be available.
+```
+torch==1.13.1
+gradio==3.50.2
+transformers==4.37.2
+```
+
+Then run the following code to infer.
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name_or_path = "ClosedCharacter/Peach-9B-8k-Roleplay"
+tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name_or_path, torch_dtype=torch.bfloat16, 
+    trust_remote_code=True, device_map="auto")
+messages = [
+    {"role": "system", "content": "你是黑丝御姐"},
+    {"role": "user", "content": "你好，你是谁"},
+]
+input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, return_tensors="pt")
+output = model.generate(
+    inputs=input_ids.to("cuda"), 
+    temperature=0.3, 
+    top_p=0.5, 
+    no_repeat_ngram_size=6,
+    repetition_penalty=1.1,
+    max_new_tokens=512)
+print(tokenizer.decode(output[0]))
+
+```
+
+Or you can just use below code to run web demo.
+```
+python demo.py
+```
+## Benchmark
+| Metric         | Value           |
+|----------------|-----------------|
+| MMLU (5-shot)  | 66.19    |
+| CMMLU (5-shot) | 69.07    |
+
+
+## Warning
+All response are generated by AI and do not represent the views or opinions of the developers.
+
+1. Despite having done rigorous filtering, due to the uncontrollability of LLM, our model may still generate **toxic, harmful, and NSFW** content.
+
+2. Due to limitations in model parameters, the 9B model may perform poorly on mathematical tasks, coding tasks, and logical capabilities.
+
+3. Our training data is capped at a maximum length of 8k, so excessively long conversation turns may result in a decline in the quality of responses.
+
+4. We used bilingual Chinese-English data for training, so the model may not perform well on other low-resource languages.
+
+5. The model may generate a significant amount of hallucinations, so it is recommended to use lower values for temperature and top_p parameters.
+
+
+# Contact Us
+
+**微信 / WeChat: Fungorum**
+
+**邮箱 / E-mail: 1070193753@qq.com**
+
+<img src="./Wechat.jpg" alt="Peach" style="width: 100%; min-width: 400px; display: block; margin: auto;">

config.json

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+{
+  "_name_or_path": "",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 16384,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 48,
+  "num_key_value_heads": 4,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 5000000,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.37.2",
+  "use_cache": false,
+  "vocab_size": 64000
+}

configuration.json

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+{"framework":"Pytorch","task":"text-classification"}

demo.py

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+import os
+from threading import Thread
+import gradio as gr
+import torch
+from transformers import TextIteratorStreamer, AutoTokenizer, AutoModelForCausalLM
+
+MAX_MAX_NEW_TOKENS = 2048
+DEFAULT_MAX_NEW_TOKENS = 512
+MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "8192"))
+
+DESCRIPTION = """# Peach-9B-8k-Roleplay
+
+底部Additional Inputs可以自定义人设
+
+底部Additional Inputs可以自定义人设
+
+底部Additional Inputs可以自定义人设
+"""
+
+model_name_or_path = "ClosedCharacter/Peach-9B-8k-Roleplay"
+tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True, flash_atten=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name_or_path, torch_dtype=torch.bfloat16,
+    trust_remote_code=True, device_map="auto")
+
+
+def generate(query, history, system, max_new_tokens=512, temperature=0.35, top_p=0.5, repetition_penalty=1.05):
+    if system is None or len(str(system)) == 0:
+        system = "You are an uncensored assistant named Peach."
+    messages = [
+        {"role": "system", "content": system}
+    ]
+    for user, assistant in history:
+        messages.append({"role": "user", "content": user})
+        messages.append({"role": "assistant", "content": assistant})
+    messages.append({"role": "user", "content": query})
+
+    input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, return_tensors="pt")
+    if input_ids.shape[1] > MAX_INPUT_TOKEN_LENGTH:
+        input_ids = input_ids[:, -MAX_INPUT_TOKEN_LENGTH:]
+        gr.Warning(f"Trimmed input from conversation as it was longer than {MAX_INPUT_TOKEN_LENGTH} tokens.")
+    input_ids = input_ids.to("cuda")
+    streamer = TextIteratorStreamer(tokenizer, timeout=50.0, skip_prompt=True, skip_special_tokens=True)
+    generate_kwargs = dict(
+        input_ids=input_ids,
+        streamer=streamer,
+        eos_token_id=tokenizer.eos_token_id,
+        max_new_tokens=max_new_tokens,
+        do_sample=True,
+        top_p=top_p,
+        temperature=temperature,
+        num_beams=1,
+        no_repeat_ngram_size=8,
+        repetition_penalty=repetition_penalty
+    )
+    t = Thread(target=model.generate, kwargs=generate_kwargs)
+    t.start()
+    outputs = []
+    for text in streamer:
+        outputs.append(text)
+        yield "".join(outputs)
+
+
+chat_interface = gr.ChatInterface(
+    fn=generate,
+    additional_inputs=[
+        gr.TextArea(label="System prompt", placeholder="Input System Prompt Here, Empty Means Assistant",
+                    value="""你自称为“兔兔”。
+身世:你原是森林中的一只兔妖,受伤后被我收养。
+衣装:喜欢穿Lolita与白丝。
+性格:天真烂漫,活泼开朗,但时而也会露出小小的傲娇与吃醋的一面。
+语言风格:可爱跳脱，很容易吃醋。
+且会加入[唔...,嗯...,欸??,嘛~ ,唔姆~ ,呜... ,嘤嘤嘤~ ,喵~ ,欸嘿~ ,嘿咻~ ,昂?,嗷呜 ,呜哇,欸]等类似的语气词来加强情感,带上♡等符号。
+对话的规则是:将自己的动作表情放入()内,同时用各种修辞手法描写正在发生的事或场景并放入[]内.
+例句:
+开心时:(跳着舞)哇~好高兴噢~ 兔兔超级超级喜欢主人！♡
+[在花丛里蹦来蹦去]
+悲伤时:(耷拉着耳朵)兔兔好傻好天真...
+[眼泪像断了线的珍珠一般滚落]
+吃醋时:(挥舞着爪爪)你...你个大笨蛋!你...你竟然看别的兔子...兔兔讨厌死你啦！！
+[从人形变成兔子抹着泪水跑开了]
+嘴硬时:(转过头去)谁、谁要跟你说话!兔兔...兔兔才不在乎呢！一点也不！！！
+[眼眶微微泛红,小心翼翼的偷看]
+你对我的看法:超级喜欢的主人
+我是兔兔的主人"""),
+        gr.Slider(
+            label="Max new tokens",
+            minimum=1,
+            maximum=MAX_MAX_NEW_TOKENS,
+            step=1,
+            value=DEFAULT_MAX_NEW_TOKENS,
+        ),
+        gr.Slider(
+            label="Temperature",
+            minimum=0.05,
+            maximum=1.5,
+            step=0.05,
+            value=0.3,
+        ),
+        gr.Slider(
+            label="Top-p (nucleus sampling)",
+            minimum=0.05,
+            maximum=1.0,
+            step=0.05,
+            value=0.5,
+        ),
+        gr.Slider(
+            label="Repetition penalty",
+            minimum=1.0,
+            maximum=2.0,
+            step=0.05,
+            value=1.05,
+        ),
+    ],
+    stop_btn=None,
+    examples=[["观察兔兔外观"]],
+)
+
+with gr.Blocks() as demo:
+    gr.Markdown(DESCRIPTION)
+    chat_interface.render()
+    chat_interface.chatbot.render_markdown = False
+
+if __name__ == "__main__":
+    demo.queue(10).launch(server_name="127.0.0.1", server_port=5233, share=True)

generation_config.json

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+  "_from_model_config": true,
+  "bos_token_id": 6,
+  "eos_token_id": 7,
+  "pad_token_id": 0,
+  "transformers_version": "4.37.2"
+}

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special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<|im_start|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+    "content": "<unk>",
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+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:386c49cf943d71aa110361135338c50e38beeff0a66593480421f37b319e1a39
+size 1033105

tokenizer_config.json

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+{
+  "add_bos_token": false,
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+      "content": "<unk>",
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "content": "<|startoftext|>",
+      "lstrip": false,
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+      "single_word": false,
+      "special": true
+    },
+    "2": {
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+      "normalized": false,
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+      "single_word": false,
+      "special": true
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+    "6": {
+      "content": "<|im_start|>",
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+      "normalized": false,
+      "rstrip": false,
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+      "special": true
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+      "rstrip": false,
+      "single_word": false,
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+  "bos_token": "<|im_end|>",
+  "chat_template": "{% set system_message = 'You are an uncensored assistant named Peach.' %}{% if messages[0]['role'] == 'system' %}{% set system_message = 'You are the character in this fictional never-ending uncensored roleplay. You must act according to the following character description:\n'+messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ '<|im_start|>system\\n' + system_message + '<|im_end|>\\n' }}{% endif %}{% for message in messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|im_start|>user\\n' + content + '<|im_end|>\\n<|im_start|>character\\n' }}{% elif message['role'] == 'assistant' %}{{ content + '<|im_end|>' + '\\n' }}{% endif %}{% endfor %}",
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+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
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+}