| license: apache-2.0 | |
| language: | |
| - en | |
| # **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. |