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metadata
license: other
license_name: qwen
license_link: >-
  https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT
language:
  - en
  - zh
library_name: transformers
pipeline_tag: text-generation
inference: false
tags:
  - llama
  - qwen

This is the LLaMAfied version of Qwen-14B-Chat model by Alibaba Cloud.

This model is converted with https://github.com/hiyouga/LLaMA-Factory/blob/main/tests/llamafy_qwen.py

The tokenizer is borrowed from https://huggingface.co/CausalLM/72B-preview-llamafied-qwen-llamafy

You may use this model for fine-tuning in downstream tasks, we recommend using our efficient fine-tuning toolkit. https://github.com/hiyouga/LLaMA-Factory

Usage:

from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer

tokenizer = AutoTokenizer.from_pretrained("hiyouga/Qwen-14B-Chat-LLaMAfied")
model = AutoModelForCausalLM.from_pretrained("hiyouga/Qwen-14B-Chat-LLaMAfied", torch_dtype="auto", device_map="auto")
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)

query = (
    "<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n"
    "<|im_start|>user\nWho are you?<|im_end|>\n"
    "<|im_start|>assistant\n"
)
inputs = tokenizer([query], return_tensors="pt")
inputs = inputs.to("cuda")
generate_ids = model.generate(**inputs, eos_token_id=[151643, 151645], max_new_tokens=256, streamer=streamer)

You could also alternatively launch a CLI demo by using the script in LLaMA-Factory

python src/cli_demo.py --template qwen --model_name_or_path hiyouga/Qwen-14B-Chat-LLaMAfied