1. Model Details
Introducing xinchen9/llama3-b8-ft, an advanced language model comprising 8 billion parameters. It has been fine-trained based on meta-llama/Meta-Llama-3.1-8B.
The llama3-b8 model was fine-tuning on dataset CoT_ollection.
2. How to Use
Here give some examples of how to use our model.
Text Completion
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
model_name = "xinchen9/Llama3.1_CoT"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id
3 Disclaimer
The license on this model does not constitute legal advice. We are not responsible for the actions of third parties who use this model. Please cosult an attorney before using this model for commercial purposes.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 13.35 |
| IFEval (0-Shot) | 22.46 |
| BBH (3-Shot) | 19.90 |
| MATH Lvl 5 (4-Shot) | 1.51 |
| GPQA (0-shot) | 5.15 |
| MuSR (0-shot) | 11.77 |
| MMLU-PRO (5-shot) | 19.32 |