README.md

---
language:
- en
license: apache-2.0
model-index:
- name: luxia-21.4b-alignment-v1.0
  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: 77.47
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=saltlux/luxia-21.4b-alignment-v1.0
      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: 91.88
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=saltlux/luxia-21.4b-alignment-v1.0
      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: 68.1
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=saltlux/luxia-21.4b-alignment-v1.0
      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: 79.17
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=saltlux/luxia-21.4b-alignment-v1.0
      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: 87.45
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=saltlux/luxia-21.4b-alignment-v1.0
      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: 62.4
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=saltlux/luxia-21.4b-alignment-v1.0
      name: Open LLM Leaderboard
---

# **Introduction**
We introduce luxia-21.4b-alignment-v1.0, an instruction-tuned and alignment model based on luxia-21.4b.
Please refer to the evaluation results table for details.

# **Instruction Fine-tuning Strategy**
We utilize state-of-the-art instruction fine-tuning methods including supervised fine-tuning (SFT) and direct preference optimization (DPO)

# **Data Contamination Test Results**
Results will be updated soon.

# **Evaluation Results**
Results will be updated soon.


# **Usage Instructions**

### **How to use**
```python
# pip install transformers==4.35.2
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("saltlux/luxia-21.4b-alignment-v0.1")
model = AutoModelForCausalLM.from_pretrained(
    "saltlux/luxia-21.4b-alignment-v0.1",
    device_map="auto",
    torch_dtype=torch.float16,
)
```

### **License**
- [saltlux/luxia-21.4b-alignment-v1.0](https://huggingface.co/saltlux/luxia-21.4b-alignment-v1.0): apache-2.0


### **Contact Us** ###
Any questions and suggestions are welcomed at the discussion tab.
# [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_saltlux__luxia-21.4b-alignment-v1.0)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |77.74|
|AI2 Reasoning Challenge (25-Shot)|77.47|
|HellaSwag (10-Shot)              |91.88|
|MMLU (5-Shot)                    |68.10|
|TruthfulQA (0-shot)              |79.17|
|Winogrande (5-shot)              |87.45|
|GSM8k (5-shot)                   |62.40|