Instructions to use janny127/TrainedModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use janny127/TrainedModel with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "janny127/TrainedModel") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-12/trainer_state.json from janny127/TrainedModel: direct link, hf CLI and curl.
- Browser
- Download file 885 Bytes
-
https://huggingface.co/janny127/TrainedModel/resolve/main/checkpoint-12/trainer_state.json
- Command line
-
hf download hf://janny127/TrainedModel/checkpoint-12/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/janny127/TrainedModel/resolve/main/checkpoint-12/trainer_state.json
885 Bytes
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 3.0, | |
| "eval_steps": 500, | |
| "global_step": 12, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 1.0, | |
| "grad_norm": 1.2067400217056274, | |
| "learning_rate": 2.4e-05, | |
| "loss": 1.4814, | |
| "step": 4 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "grad_norm": 0.9487990140914917, | |
| "learning_rate": 1.2e-05, | |
| "loss": 1.3757, | |
| "step": 8 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "grad_norm": 0.457656592130661, | |
| "learning_rate": 0.0, | |
| "loss": 1.3112, | |
| "step": 12 | |
| } | |
| ], | |
| "logging_steps": 4, | |
| "max_steps": 12, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 3, | |
| "save_steps": 500, | |
| "total_flos": 857663889997824.0, | |
| "train_batch_size": 2, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |