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---
license: mit
language:
- ja
---
# Overview
This model generates text like viewer comments in live streaming, such as Youtube Live.
This model was trained on [rinna/japanese-gpt-neox-3.6b-instruction-ppo](https://huggingface.co/rinna/japanese-gpt-neox-3.6b-instruction-ppo) using Lora.
# How to use the model
~~~~python
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("rinna/japanese-gpt-neox-3.6b-instruction-ppo", use_fast=False)
model = AutoModelForCausalLM.from_pretrained("rinna/japanese-gpt-neox-3.6b-instruction-ppo", torch_dtype=torch.float16, device_map="auto")
from peft import PeftModel
peft_model = PeftModel.from_pretrained(model, "oshizo/comment-generation-japanese-3.6b-lora", device_map="auto")
prompt = f"ユーザー: 今朝うちの小さな畑でトマトがね、いい感じに赤くなってたんだよね。そのまま通学路を歩いてたんだけどさ、一つちぎって弁当に入れておけば良かっな~と思って。トマト可愛くて好き。<NL>システム: "
token_ids = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
with torch.no_grad():
output_ids = model.generate(
token_ids.to(model.device),
do_sample=True,
max_new_tokens=32,
num_return_sequences=4,
pad_token_id=tokenizer.pad_token_id,
bos_token_id=tokenizer.bos_token_id,
eos_token_id=tokenizer.eos_token_id
)
for output in output_ids.tolist():
print(tokenizer.decode(output[token_ids.size(1):], skip_special_tokens=True))
# これから剥くの面倒くさいよ<NL>
# なんやその可愛い好きは<NL>
# 冷やしておくと美味しいよな<NL>
# 食レポ具体的に<NL>
~~~~
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