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AISquare-Instruct-SOLAR-10.7b-v0.5.32

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AISquare-Instruct-SOLAR-10.7b-v0.5.32
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---
language:
- en
license: cc-by-nc-4.0
pipeline_tag: text-generation
model-index:
- name: AISquare-Instruct-SOLAR-10.7b-v0.5.32
  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: 61.86
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kimwooglae/AISquare-Instruct-SOLAR-10.7b-v0.5.32
      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: 84.66
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kimwooglae/AISquare-Instruct-SOLAR-10.7b-v0.5.32
      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: 63.13
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kimwooglae/AISquare-Instruct-SOLAR-10.7b-v0.5.32
      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: 51.19
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kimwooglae/AISquare-Instruct-SOLAR-10.7b-v0.5.32
      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: 82.79
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kimwooglae/AISquare-Instruct-SOLAR-10.7b-v0.5.32
      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: 15.09
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kimwooglae/AISquare-Instruct-SOLAR-10.7b-v0.5.32
      name: Open LLM Leaderboard
---

# AISquare-Instruct-SOLAR-10.7b-v0.5.32
  
## Model Details

**Developed by** 
[Inswave Systems](https://www.inswave.com) UI Platform Team

**Base Model**
[upstage/SOLAR-10.7B-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-v1.0)

   
# Implementation Code
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

repo = "kimwooglae/AISquare-Instruct-SOLAR-10.7b-v0.5.32"
model = AutoModelForCausalLM.from_pretrained(
        repo,
        return_dict=True,
        torch_dtype=torch.float16,
        device_map='auto'
)
tokenizer = AutoTokenizer.from_pretrained(repo)
```

---
# [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_kimwooglae__AISquare-Instruct-SOLAR-10.7b-v0.5.32)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |59.79|
|AI2 Reasoning Challenge (25-Shot)|61.86|
|HellaSwag (10-Shot)              |84.66|
|MMLU (5-Shot)                    |63.13|
|TruthfulQA (0-shot)              |51.19|
|Winogrande (5-shot)              |82.79|
|GSM8k (5-shot)                   |15.09|