Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +92 -0
- config.json +32 -0
- generation_config.json +11 -0
- model-00001-of-00006.safetensors +3 -0
- model-00002-of-00006.safetensors +3 -0
- model-00003-of-00006.safetensors +3 -0
- model-00004-of-00006.safetensors +3 -0
- model-00005-of-00006.safetensors +3 -0
- model-00006-of-00006.safetensors +3 -0
- model.safetensors.index.json +586 -0
- special_tokens_map.json +23 -0
- tokenizer.json +3 -0
- tokenizer_config.json +196 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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library_name: transformers
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tags:
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- unsloth
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- trl
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- sft
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---
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# Model Card for Model ID
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根据小红书数据微调的专用于书写小红书文案的R1模型
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## Training at Chongqing Valiant Cat
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This model was trained by the AI Laboratory of Chongqing Valiant Cat Technology Co., LTD(```https://vvicat.com/```).Business cooperation is welcome
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### Direct Use
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```
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from transformers import TextStreamer
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from unsloth import FastLanguageModel
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model_name = "starsfriday/DeepSeek-R1-Distill-Qwen-xhs-14B"
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model, tokenizer = FastLanguageModel.from_pretrained(
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model_name=model_name,
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max_seq_length=8192,
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load_in_4bit=True
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)
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FastLanguageModel.for_inference(model)
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question = "写一篇小红书风格的帖子,标题是男生变帅只需三步丨分享逆袭大干货"
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inputs = tokenizer([question], return_tensors="pt").to("cuda")
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streamer = TextStreamer(tokenizer)
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_ = model.generate(
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**inputs,
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streamer=streamer,
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max_new_tokens=1200,
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use_cache=True
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)
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```
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```
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<think>
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好的,用户让我写一篇小红书风格的帖子,标题是“男生变帅只需三步丨分享逆袭大干货”。首先,我需要确定目标受众。小红书的用户主要是年轻女性,但这个主题是针对男生变帅的,所以可能吸引男性读者,尤其是那些想要提升自己外在形象的人。
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接下来,我要考虑小红书帖子的特点。通常这类平台喜欢用活泼、亲切的语气,使用表情符号和分段清晰的内容结构。标题需要吸引眼球,所以用了“逆袭大干货”这样的词汇,带有激励的感觉。正文部分应该分步骤说明,每一步都有具体的建议,并且加入一些实用的小贴士。
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用户的需求是让男生通过三个步骤变帅,可能他们希望内容简单易行,不需要太多时间和金钱投入。因此,我需要确保每个步骤都是可行的,比如日常习惯、发型和穿搭,这些都是比较基础但有效的方面。
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然后,我要考虑可能没有明说的深层需求。也许有些男生觉得变帅很难,或者不知道从哪里下手,所以需要提供一个清晰的框架,让他们感觉只要跟着做就能看到效果。同时,加入一些鼓励的话语,比如“30天养成”这样的时间点,增加紧迫感和动力。
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另外,要注意避免过于专业的术语,保持语言通俗易懂。使用表情符号来增加亲和力,比如🔥、💡这些符号可以突出重点。每个步骤下还要有具体的例子,比如发型推荐或者穿搭建议,这样读者更容易理解和应用。
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最后,检查结构是否符合小红书的风格:标题吸引人,正文分点明确,每部分有小标题,结尾有互动引导,比如让读者留言分享自己的经验或提问。确保整体内容积极向上,充满正能量,符合平台调性。
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</think>
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【男生变帅只需三步丨30天逆袭被夸“脱胎换骨”!】🔥
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|
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✨“你真的不需要花1w买奢侈品,
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每天5分钟习惯+20秒打理=素颜也能赢!”
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(附私藏干货图解版)
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|
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💡Step 1|「气质感从洗脸开始」
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✅每日3步水煮蛋法则:
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1️⃣ 温和洁面后用氨基酸洗面奶按压T区(拒绝搓脸!)
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2️⃣ 精华+乳液按摩至吸收,男生选含烟酰胺/玻尿酸款更清爽
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3️⃣ 每周1次泥膜敷鼻翼闭口区(黑头退退退!)
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|
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💡Step 2|「发型决定颜值高度」
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✅冷门但显帅王炸公式:
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✔️短发男生:C字内扣+侧分刘海=瞬间变清爽学长
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✔️中长发男生:背 undercut + 长卷度(理发店说“韩系慵懒风”就行)
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✔️油头星人必备:摩丝定型+喷雾锁死,拒绝塌鼻子!
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+
|
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💡Step 3|「穿搭心机藏在细节里」
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✅5件万能搭法则:
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1️⃣ 白衬衫+牛仔裤=永不出错基础款
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2️⃣ 毛衣配工装裤(记得露脚踝!)
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3️⃣ 卫衣叠穿技巧:内搭短袖+外挂高领打底
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4️⃣ 配饰小心机:银色耳钉/卡西欧表/帆布鞋
|
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+
5️⃣ 背包选帆布款,装书本也像在背奢侈品
|
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+
|
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🌟私藏tips:
|
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✔️每天照镜子时微笑3分钟(提升眼周紧致度)
|
83 |
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✔️饮食加点深海鱼油+维生素E胶囊(改善暗沉发黄)
|
84 |
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✔️周末去健身房打个篮球(汗液能打开毛孔吸收护肤品)
|
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+
|
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+
👉🏻30天打卡挑战:评论区交作业的宝子记得@我!
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(悄悄说:连我的直男同事都问我是不是偷偷打了玻尿酸…)
|
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|
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#男生变帅 #逆袭干货 #形象管理 #学渣逆袭 #小红书成长记
|
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```
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config.json
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{
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"_name_or_path": "/root/autodl-tmp/models/DeepSeek-R1-Distill-Qwen-14B",
|
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"architectures": [
|
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"Qwen2ForCausalLM"
|
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],
|
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"attention_dropout": 0.0,
|
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"bos_token_id": 151646,
|
8 |
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"eos_token_id": 151643,
|
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"hidden_act": "silu",
|
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"hidden_size": 5120,
|
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"initializer_range": 0.02,
|
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"intermediate_size": 13824,
|
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"max_position_embeddings": 131072,
|
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"max_window_layers": 48,
|
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"model_type": "qwen2",
|
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"num_attention_heads": 40,
|
17 |
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"num_hidden_layers": 48,
|
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"num_key_value_heads": 8,
|
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"pad_token_id": 151654,
|
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"rms_norm_eps": 1e-05,
|
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"rope_scaling": null,
|
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"rope_theta": 1000000.0,
|
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"sliding_window": null,
|
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"tie_word_embeddings": false,
|
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"torch_dtype": "bfloat16",
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"transformers_version": "4.48.3",
|
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"unsloth_fixed": true,
|
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"unsloth_version": "2025.2.4",
|
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"use_cache": true,
|
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"use_sliding_window": false,
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"vocab_size": 152064
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 151646,
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"do_sample": true,
|
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"eos_token_id": 151643,
|
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"max_length": 131072,
|
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"pad_token_id": 151654,
|
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+
"temperature": 0.6,
|
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"top_p": 0.95,
|
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"transformers_version": "4.48.3"
|
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}
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model-00001-of-00006.safetensors
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model-00002-of-00006.safetensors
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model.safetensors.index.json
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159 |
+
"content": "<|fim_pad|>",
|
160 |
+
"lstrip": false,
|
161 |
+
"normalized": false,
|
162 |
+
"rstrip": false,
|
163 |
+
"single_word": false,
|
164 |
+
"special": false
|
165 |
+
},
|
166 |
+
"151663": {
|
167 |
+
"content": "<|repo_name|>",
|
168 |
+
"lstrip": false,
|
169 |
+
"normalized": false,
|
170 |
+
"rstrip": false,
|
171 |
+
"single_word": false,
|
172 |
+
"special": false
|
173 |
+
},
|
174 |
+
"151664": {
|
175 |
+
"content": "<|file_sep|>",
|
176 |
+
"lstrip": false,
|
177 |
+
"normalized": false,
|
178 |
+
"rstrip": false,
|
179 |
+
"single_word": false,
|
180 |
+
"special": false
|
181 |
+
}
|
182 |
+
},
|
183 |
+
"bos_token": "<|begin▁of▁sentence|>",
|
184 |
+
"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<|User|>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<|Assistant|><|tool▁calls▁begin|><|tool▁call▁begin��>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<|tool▁call▁end|>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<|tool▁call▁end|>'}}{{'<|tool▁calls▁end|><|end▁of▁sentence|>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<|tool▁outputs▁end|>' + message['content'] + '<|end▁of▁sentence|>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<|Assistant|>' + content + '<|end▁of▁sentence|>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<|tool▁outputs▁begin|><|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<|tool▁outputs▁end|>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<|Assistant|><think>\\n'}}{% endif %}",
|
185 |
+
"clean_up_tokenization_spaces": false,
|
186 |
+
"eos_token": "<|end▁of▁sentence|>",
|
187 |
+
"extra_special_tokens": {},
|
188 |
+
"legacy": true,
|
189 |
+
"model_max_length": 131072,
|
190 |
+
"pad_token": "<|vision_pad|>",
|
191 |
+
"padding_side": "left",
|
192 |
+
"sp_model_kwargs": {},
|
193 |
+
"tokenizer_class": "LlamaTokenizer",
|
194 |
+
"unk_token": null,
|
195 |
+
"use_default_system_prompt": false
|
196 |
+
}
|