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
| { | |
| "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 | |
| } | |
| } |