scriptGenGLM1.0

模型用于中文剧本生成，用户通过与模型交互生成剧本。

Model Details

Model Description

用户与模型交互例子：用户输入：人物简介：关羽：正直善良的性格。母亲：坚强不妥协的妇人家。父亲：为国牺牲的好男儿。剧情大纲：第一集：xxxx:讲述在xxxxxx。

Developed by: Xinrui Li(Relee)
Language(s) (NLP): Chinese
License: Apache License Version 2.0
Finetuned from model: chatglm3-6b

Model Sources [optional]

Repository: https://github.com/releerr/ScriptGenGLM.git

Direct Use

请注意，该模型基于chatglm3-6b模型进行微调，我们并没有合并训练后的模型，而是在adapterconfig.json中记录了微调型的路径。您需要首先部署好chatglm3-6b模型后，将adapterconfig.json中basemodelnameorpath的路径修改为您部署chatglm3-6b模型的路径。

from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.frompretrained("outputNOEnter/checkpoint-3000", trustremotecode=True) model = AutoModel.frompretrained("outputNOEnter/checkpoint-3000", trustremotecode=True, device='cuda') model = model.eval() response, history = model.chat(tokenizer, "你好,你可以根据我提供的信息以Markdown格式写一集剧本吗？要求300字以内。", history=[]) print("\n\n"+response) response, history = model.chat(tokenizer, "人物简介：我（孟刚）：战火中成长，后成为团长为国奉献牺。母亲：坚强不妥协的妇人家。父亲：为国牺牲的好男儿。桃子：我的妻子，坚守家园，等待我（孟刚）的归来。剧情大纲：第一集：你带我回家: 讲述在抗美援朝时期，孟刚的父亲在前线牺牲，母亲在废墟中悲痛欲绝，带着年幼的孟刚踏上了归途。", history=[]) print("\n\n"+response)

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

Framework versions

PEFT 0.10.0

剧本生成器

作品详情