Instructions to use Serega6678/tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Serega6678/tmp with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "Serega6678/tmp") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 1.0, | |
| "eval_loss": 1.0098061561584473, | |
| "eval_runtime": 480.2819, | |
| "eval_samples": 6440, | |
| "eval_samples_per_second": 13.409, | |
| "eval_steps_per_second": 0.839 | |
| } |