Instructions to use yhc2222/tsp_llama8b_accord_r64_sample5000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- Unsloth Desktop
TSP LLaMA 8B Fine-tuned Model
Model Description
Traveling Salesman Problem (TSP) ์ต์ ํ๋ฅผ ์ํด ํ์ธํ๋๋ LLaMA 8B ๋ชจ๋ธ์ ๋๋ค.
Training Details
- Base Model: unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit
- LoRA Rank: 64
- Epochs: 2
- Max Sequence Length: 40,000
- Dataset: ACCORD
Usage
from unsloth import FastLanguageModel
model, tokenizer = FastLanguageModel.from_pretrained(
model_name="yhc2222/tsp_llama8b_accord_r64_sample5000",
max_seq_length=40000,
load_in_4bit=True,
dtype=torch.bfloat16,
)
FastLanguageModel.for_inference(model)
Model tree for yhc2222/tsp_llama8b_accord_r64_sample5000
Base model
meta-llama/Llama-3.1-8B Finetuned
meta-llama/Llama-3.1-8B-Instruct