Instructions to use Likich/open-coding-qwen25_7b-single_code-qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Likich/open-coding-qwen25_7b-single_code-qlora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-7B-Instruct") model = PeftModel.from_pretrained(base_model, "Likich/open-coding-qwen25_7b-single_code-qlora") - Notebooks
- Google Colab
- Kaggle
File size: 510 Bytes
a8231a2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"base_model": "Qwen/Qwen2.5-7B-Instruct",
"adapter_name": "qwen25_7b",
"task_mode": "single_code",
"training_rows": 799,
"validation_rows": 100,
"settings": {
"epochs": 3.0,
"learning_rate": 0.0002,
"batch_size": 8,
"gradient_accumulation_steps": 1,
"max_length": 1024,
"lora_r": 16,
"lora_alpha": 32,
"lora_dropout": 0.05,
"warmup_ratio": 0.03,
"logging_steps": 10,
"save_total_limit": 2,
"seed": 42,
"packing": false,
"resume": true
}
} |