README.md

metadata

language:
  - en
  - zh
license: other
library_name: transformers
tags:
  - llama
  - qwen
license_name: qwen
license_link: >-
  https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT
pipeline_tag: text-generation
inference: false
model-index:
  - name: Qwen-14B-Chat-LLaMAfied
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: AI2 Reasoning Challenge (25-Shot)
          type: ai2_arc
          config: ARC-Challenge
          split: test
          args:
            num_few_shot: 25
        metrics:
          - type: acc_norm
            value: 57.51
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=hiyouga/Qwen-14B-Chat-LLaMAfied
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: HellaSwag (10-Shot)
          type: hellaswag
          split: validation
          args:
            num_few_shot: 10
        metrics:
          - type: acc_norm
            value: 82.11
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=hiyouga/Qwen-14B-Chat-LLaMAfied
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU (5-Shot)
          type: cais/mmlu
          config: all
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 65.57
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=hiyouga/Qwen-14B-Chat-LLaMAfied
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: TruthfulQA (0-shot)
          type: truthful_qa
          config: multiple_choice
          split: validation
          args:
            num_few_shot: 0
        metrics:
          - type: mc2
            value: 51.99
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=hiyouga/Qwen-14B-Chat-LLaMAfied
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: Winogrande (5-shot)
          type: winogrande
          config: winogrande_xl
          split: validation
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 72.93
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=hiyouga/Qwen-14B-Chat-LLaMAfied
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GSM8k (5-shot)
          type: gsm8k
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 39.5
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=hiyouga/Qwen-14B-Chat-LLaMAfied
          name: Open LLM Leaderboard

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

• Developed by: Alibaba Cloud.
• Language(s) (NLP): Chinese/English
• License: Tongyi Qianwen License

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)

messages = [
    {"role": "user", "content": "Who are you?"}
]
inputs = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")
inputs = inputs.to("cuda")
generate_ids = model.generate(inputs, 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

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	61.60
AI2 Reasoning Challenge (25-Shot)	57.51
HellaSwag (10-Shot)	82.11
MMLU (5-Shot)	65.57
TruthfulQA (0-shot)	51.99
Winogrande (5-shot)	72.93
GSM8k (5-shot)	39.50