waka-gpt is a GPT-based language model designed for Japanese text generation. It was constructed by fine-tuning the original base model, rinna/japanese-gpt2-small (based on base model information). Features and Use Cases (Samples): Generating classical and waka-style texts Generating Japanese poetry and creative writing Conversation/Creative writing assistance

Developed by: supertakerin2
Funded by: No one
Shared by: No one
Model type: Text-generation
Language(s) (NLP): Japanese,Classical Japanese
License: Mit License
Finetuned from model : rinna/japanese-gpt2-small

Model Sources

The Eight Imperially Compiled Anthologies of Waka Poetry, compiled during the golden age of waka culture

Direct Uses

python

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("supertakerin2/waka-gpt")
model = AutoModelForCausalLM.from_pretrained("supertakerin2/waka-gpt")

input_text = "古き良き日本の風景を詠む和歌："
inputs = tokenizer(input_text, return_tensors="pt")

outputs = model.generate(**inputs, max_length=100)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Bias, Risks, and Limitations

waka-gpt is a statistical language model trained on large volumes of text, and the following points require attention: Potential for factual errors in output Potential for inclusion of biases Potential to generate inappropriate expressions in specific contexts Proper filtering and operation under supervision are recommended.

Model Card Contact

xianghuangwugn@gmail.com