language, license, base_model, pipeline_tag, tags
| language | license | base_model | pipeline_tag | tags | |||||
|---|---|---|---|---|---|---|---|---|---|
|
apache-2.0 | Qwen/Qwen2.5-0.5B | text-generation |
|
Tangshi|中文唐诗生成模型
基于Qwen2.5-0.5B微调的古诗专用大模型,擅长自动生成五言/七言绝句、律诗,专为古典诗词创作优化。训练数据为57000首唐诗全参数。
仓库信息
Huggingface地址:Emaoso/Tangshi
包含两类权重:
model.safetensors:原生transformers权重,用于Python代码调用model-ollama.gguf:GGUF量化权重,用于Ollama本地部署 附带:Ollama一键构建配置 Modelfile
一、Python Transformers调用(推荐)
1.安装依赖
pip install torch transformers
====================================
代码示例
from transformers import AutoTokenizer, AutoModelForCausalLM
model_name = "Emaoso/Tangshi"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
# 写诗指令
prompt = "写一首春日五言绝句"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=80)
result = tokenizer.decode(outputs[0], skip_special_tokens=True)
# 清洗多余注释
import re
result = re.sub(r'(.*|〖.*|见卷.*','',result)
print(result)
======================================
ollama 使用
ollama create tangshi https://huggingface.co/Emaoso/Tangshi/resolve/main/Modelfile
ollama run tangshi
Description