Instructions to use Vinitha2004/qwen2.5-coder-3b-instruct-awq-final-working_draft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Vinitha2004/qwen2.5-coder-3b-instruct-awq-final-working_draft with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-3B-Instruct-AWQ") model = PeftModel.from_pretrained(base_model, "Vinitha2004/qwen2.5-coder-3b-instruct-awq-final-working_draft") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 3, | |
| "checkpoint_type": "epoch", | |
| "is_best": false, | |
| "validation_metrics": { | |
| "total": 1.6648176369258776, | |
| "distill": 0.4663255028366465, | |
| "super": 24.436167814042147 | |
| }, | |
| "training_metrics": { | |
| "total": 1.6754711744398976, | |
| "distill": 0.48240784243990176, | |
| "super": 24.343674139487042 | |
| }, | |
| "hyperparameters": { | |
| "temperature": 2.0, | |
| "alpha": 0.95, | |
| "learning_rate": 0.001, | |
| "batch_size": 1, | |
| "gradient_accumulation_steps": 16 | |
| }, | |
| "best_val_loss_so_far": 1.6648216817606247, | |
| "best_epoch_so_far": 1, | |
| "patience_counter": 1, | |
| "save_time": "2025-06-13 19:03:51" | |
| } |