Instructions to use yashss/Phi-3-mini-128k-instruct_fineTuned_45ee384b-cd44-476e-a2eb-83113340845b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use yashss/Phi-3-mini-128k-instruct_fineTuned_45ee384b-cd44-476e-a2eb-83113340845b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-128k-instruct") model = PeftModel.from_pretrained(base_model, "yashss/Phi-3-mini-128k-instruct_fineTuned_45ee384b-cd44-476e-a2eb-83113340845b") - Notebooks
- Google Colab
- Kaggle
Phi-3-mini-128k-instruct_fineTuned_45ee384b-cd44-476e-a2eb-83113340845b / last-checkpoint /trainer_state.json
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 1.0, | |
| "eval_steps": 500, | |
| "global_step": 1, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [], | |
| "logging_steps": 10, | |
| "max_steps": 2, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 2, | |
| "save_steps": 500, | |
| "total_flos": 4535137953792.0, | |
| "train_batch_size": 1, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |