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
# 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: apache-2.0
Contact Us
Any questions and suggestions are welcomed at the discussion tab.
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