Instructions to use Serega6678/prototype_joint_trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Serega6678/prototype_joint_trained 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/prototype_joint_trained") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 1.0, | |
| "train_loss": 1.0006486285219118, | |
| "train_runtime": 14584.0452, | |
| "train_samples": 58034, | |
| "train_samples_per_second": 3.979, | |
| "train_steps_per_second": 0.062 | |
| } |