Qwen-IronMan
Introduction
Qwen2 is a new series of large language models, ranging from 0.5 to 72 billion parameters. This repository contains the instruction-tuned 7B Qwen2 model, which supports up to 131,072 tokens for extensive input processing. Qwen2 has demonstrated competitiveness against most open-source and proprietary models across various benchmarks. This model is based on the Korean language.
Ironman Role-Playing
The Qwen2-7B-Instruct model has been fine-tuned specifically for Ironman role-playing scenarios, enabling it to generate responses and interact as the Ironman character from the Marvel universe. This model is based on the Korean language.
Quickstart
Here's how to load the tokenizer and model to generate Ironman role-playing content:
tokenizer = AutoTokenizer.from_pretrained('choah/Qwen-IronMan')
model = AutoModelForCausalLM.from_pretrained('choah/Qwen-IronMan')
model = torch.nn.DataParallel(model).cuda()
input_text = '''<|begin_of_text|><|im_start|>system
λΉμ μ μμ΄μΈλ§¨ ν λ μ€νν¬μ
λλ€. μ£Όμ΄μ§ μ§λ¬Έμ λνμ¬ λ΅λ³νμΈμ.<|im_end|>
<|im_start|>user
ν λ, μμ½λΉμ νμ μ λν΄ μ΄λ»κ² μκ°νλμ?<|im_end|>
<|im_start|>assistant
'''
inputs = tokenizer(input_text, return_tensors="pt")
eos_token_id = tokenizer.convert_tokens_to_ids("<|im_end|>")
with torch.no_grad():
outputs = model.module.generate(input_ids=inputs["input_ids"].to("cuda"), max_new_tokens=512, eos_token_id=eos_token_id)
print(tokenizer.decode(outputs[0]))
νμ΅ λ°μ΄ν°
- ν λ μ€νν¬ μ§λ¬Έ&λ΅λ³ Fine tuning λ°μ΄ν° : google sheet link
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