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|