RichardErkhov
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README.md
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Quantization made by Richard Erkhov.
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[Github](https://github.com/RichardErkhov)
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[Discord](https://discord.gg/pvy7H8DZMG)
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[Request more models](https://github.com/RichardErkhov/quant_request)
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Yuyuan-GPT2-110M-SciFi-Chinese - GGUF
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- Model creator: https://huggingface.co/IDEA-CCNL/
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- Original model: https://huggingface.co/IDEA-CCNL/Yuyuan-GPT2-110M-SciFi-Chinese/
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| Name | Quant method | Size |
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| ---- | ---- | ---- |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q2_K.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q2_K.gguf) | Q2_K | 0.08GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q3_K_S.gguf) | Q3_K_S | 0.08GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q3_K.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q3_K.gguf) | Q3_K | 0.09GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q3_K_M.gguf) | Q3_K_M | 0.09GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q3_K_L.gguf) | Q3_K_L | 0.1GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.IQ4_XS.gguf) | IQ4_XS | 0.1GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q4_0.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q4_0.gguf) | Q4_0 | 0.1GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.IQ4_NL.gguf) | IQ4_NL | 0.1GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q4_K_S.gguf) | Q4_K_S | 0.1GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q4_K.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q4_K.gguf) | Q4_K | 0.11GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q4_K_M.gguf) | Q4_K_M | 0.11GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q4_1.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q4_1.gguf) | Q4_1 | 0.11GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q5_0.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q5_0.gguf) | Q5_0 | 0.11GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q5_K_S.gguf) | Q5_K_S | 0.11GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q5_K.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q5_K.gguf) | Q5_K | 0.12GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q5_K_M.gguf) | Q5_K_M | 0.12GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q5_1.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q5_1.gguf) | Q5_1 | 0.12GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q6_K.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q6_K.gguf) | Q6_K | 0.13GB |
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| [Yuyuan-GPT2-110M-SciFi-Chinese.Q8_0.gguf](https://huggingface.co/RichardErkhov/IDEA-CCNL_-_Yuyuan-GPT2-110M-SciFi-Chinese-gguf/blob/main/Yuyuan-GPT2-110M-SciFi-Chinese.Q8_0.gguf) | Q8_0 | 0.17GB |
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Original model description:
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---
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language:
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- zh
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inference:
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parameters:
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temperature: 1
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top_p: 0.7
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repetition_penalty: 1.1
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max_new_tokens: 128
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num_return_sequences: 3
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do_sample: true
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license: apache-2.0
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tags:
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- generate
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- gpt2
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widget:
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- 我是逻辑,面对黑暗森林法则,
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- 天空的尽头,发出了一道亮眼的光芒,
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---
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# Yuyuan-GPT2-110M-SciFi-Chinese
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- Main Page:[Fengshenbang](https://fengshenbang-lm.com/)
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- Github: [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM)
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## 简介 Brief Introduction
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基于中文版的Wenzhong-GPT2-110M,我们用接近2万的科幻小说数据进行了微调模型,让模型能够较好的续写科幻小说。
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Based on the Wenzhong-GPT2-110M, we used nearly 20000 science fiction data to fine-tune the model, so that the model can better continue to write science fiction.
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## 模型分类 Model Taxonomy
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| 需求 Demand | 任务 Task | 系列 Series | 模型 Model | 参数 Parameter | 额外 Extra |
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| :----: | :----: | :----: | :----: | :----: | :----: |
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| 科幻小说 science fiction | 自然语言生成 NLG | 余元 Yuyuan | GPT2 | 110M | 中文 Chinese |
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## 模型信息 Model Information
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模型结构和wenzhong-110M相同,只是微调的语料由通用数据变成了科幻小说。
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The structure of the model is the same as that of Wenzhong-GPT2-110M, except that the fine-tuned corpus has changed from general data to science fiction.
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## 使用 Usage
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### 加载模型 Loading Models
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```python
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from transformers import GPT2Tokenizer,GPT2LMHeadModel
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hf_model_path = 'IDEA-CCNL/Yuyuan-GPT2-110M-SciFi-Chinese'
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tokenizer = GPT2Tokenizer.from_pretrained(hf_model_path)
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model = GPT2LMHeadModel.from_pretrained(hf_model_path)
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```
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### 使用示例 Usage Examples
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```python
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question = "我是逻辑,面对黑暗森林法则,"
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inputs = tokenizer(question,return_tensors='pt')
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generation_output = model.generate(**inputs,
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return_dict_in_generate=True,
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output_scores=True,
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max_length=150,
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# max_new_tokens=80,
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do_sample=True,
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top_p = 0.6,
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# num_beams=5,
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eos_token_id=50256,
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pad_token_id=0,
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num_return_sequences = 5)
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for idx,sentence in enumerate(generation_output.sequences):
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print('next sentence %d:\n'%idx,
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tokenizer.decode(sentence).split('<|endoftext|>')[0])
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print('*'*40)
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```
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## 引用 Citation
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如果您在您的工作中使用了我们的模型,可以引用我们的[论文](https://arxiv.org/abs/2209.02970):
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If you are using the resource for your work, please cite the our [paper](https://arxiv.org/abs/2209.02970):
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```text
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@article{fengshenbang,
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author = {Jiaxing Zhang and Ruyi Gan and Junjie Wang and Yuxiang Zhang and Lin Zhang and Ping Yang and Xinyu Gao and Ziwei Wu and Xiaoqun Dong and Junqing He and Jianheng Zhuo and Qi Yang and Yongfeng Huang and Xiayu Li and Yanghan Wu and Junyu Lu and Xinyu Zhu and Weifeng Chen and Ting Han and Kunhao Pan and Rui Wang and Hao Wang and Xiaojun Wu and Zhongshen Zeng and Chongpei Chen},
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title = {Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence},
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journal = {CoRR},
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volume = {abs/2209.02970},
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year = {2022}
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}
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```
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也可以引用我们的[网站](https://github.com/IDEA-CCNL/Fengshenbang-LM/):
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You can also cite our [website](https://github.com/IDEA-CCNL/Fengshenbang-LM/):
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```text
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@misc{Fengshenbang-LM,
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title={Fengshenbang-LM},
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author={IDEA-CCNL},
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year={2021},
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howpublished={\url{https://github.com/IDEA-CCNL/Fengshenbang-LM}},
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}
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```
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