---
license: other
license_name: yi-license
license_link: LICENSE
widget:
- text: 你好! 你叫什么名字!
  output:
    text: 你好，我的名字叫聚言，很高兴见到你。
pipeline_tag: text-generation
model-index:
- name: OrionStar-Yi-34B-Chat-Llama
  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: 64.93
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OrionStarAI/OrionStar-Yi-34B-Chat-Llama
      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: 84.34
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OrionStarAI/OrionStar-Yi-34B-Chat-Llama
      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: 73.67
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OrionStarAI/OrionStar-Yi-34B-Chat-Llama
      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: 53.35
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OrionStarAI/OrionStar-Yi-34B-Chat-Llama
      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: 78.85
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OrionStarAI/OrionStar-Yi-34B-Chat-Llama
      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: 53.9
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OrionStarAI/OrionStar-Yi-34B-Chat-Llama
      name: Open LLM Leaderboard
---

[OrionStarAI/OrionStar-Yi-34B-Chat-Llama](https://huggingface.co/OrionStarAI/OrionStar-Yi-34B-Chat-Llama/tree/main) 

*This model is identical to [OrionStarAI/OrionStar-Yi-34B](https://huggingface.co/OrionStarAI/OrionStar-Yi-34B/tree/main) 
with the only difference being that the tensors have been renamed to follow the LLaMA format for automatic evaluation on the HF leaderboard.*

# Model Introduction

- OrionStar-Yi-34B-Chat from OrionStarAI is based on the open-source Yi-34B model, fine-tuned on a high-quality corpus
  of over 15 million sentences. OrionStar-Yi-34B-Chat aims to provide an excellent interactive experience for users in
  the large model community.

- The Yi series models, open-sourced by the 01-ai team, have shown impressive performance on various benchmarks in
  Chinese, English, and general domains. OrionStar-Yi-34B-Chat further explores the potential of Yi-34B. Through
  extensive fine-tuning on a large and high-quality corpus, OrionStar-Yi-34B-Chat performs exceptionally well on
  evaluation data. We strive to make it an outstanding open-source alternative in the ChatGPT domain!

- Our fine-tuned model is completely open for academic research, but please adhere to the [agreement](#license) and
  the [Yi License](https://github.com/01-ai/Yi/blob/main/MODEL_LICENSE_AGREEMENT.txt).

- Model Evaluation Results

We use [opencompass](https://opencompass.org.cn) to perform 5-shot on the following general domain datasets Testing.
The evaluation results of other models are taken
from [opencompass leaderboard](https://opencompass.org.cn/leaderboard-llm).

|                           | C-Eval    | MMLU   | CMMLU     |
|---------------------------|-----------|--------|-----------|
| **GPT-4**                 | 69.9      | **83** | 71        |
| **ChatGPT**               | 52.5      | 69.1   | 53.9      | 			
| **Claude-1**              | 52        | 65.7   | -         |
| **TigerBot-70B-Chat-V2**  | 57.7      | 65.9   | 59.9      |
| **WeMix-LLaMA2-70B**      | 55.2      | 71.3   | 56        |  			
| **LLaMA-2-70B-Chat**      | 44.3      | 63.8   | 43.3      |
| **Qwen-14B-Chat**         | 71.7      | 66.4   | 70        |
| **Baichuan2-13B-Chat**    | 56.7      | 57     | 58.4      |      	
| **OrionStar-Yi-34B-Chat** | **77.71** | 78.32  | **73.52** |  
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_OrionStarAI__OrionStar-Yi-34B-Chat-Llama)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |68.17|
|AI2 Reasoning Challenge (25-Shot)|64.93|
|HellaSwag (10-Shot)              |84.34|
|MMLU (5-Shot)                    |73.67|
|TruthfulQA (0-shot)              |53.35|
|Winogrande (5-shot)              |78.85|
|GSM8k (5-shot)                   |53.90|