Instructions to use StaAhmed/refined_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use StaAhmed/refined_model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "StaAhmed/refined_model") - Notebooks
- Google Colab
- Kaggle
Download trainer_state.json from StaAhmed/refined_model: direct link, hf CLI and curl.
- Browser
- Download file 1.2 kB
-
https://huggingface.co/StaAhmed/refined_model/resolve/main/trainer_state.json
- Command line
-
hf download hf://StaAhmed/refined_model/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/StaAhmed/refined_model/resolve/main/trainer_state.json
1.2 kB
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.9259259259259259, | |
| "global_step": 200, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.12, | |
| "learning_rate": 0.0002, | |
| "loss": 1.9564, | |
| "step": 25 | |
| }, | |
| { | |
| "epoch": 0.23, | |
| "learning_rate": 0.0002, | |
| "loss": 0.4866, | |
| "step": 50 | |
| }, | |
| { | |
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| "learning_rate": 0.0002, | |
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| "step": 75 | |
| }, | |
| { | |
| "epoch": 0.46, | |
| "learning_rate": 0.0002, | |
| "loss": 0.3118, | |
| "step": 100 | |
| }, | |
| { | |
| "epoch": 0.58, | |
| "learning_rate": 0.0002, | |
| "loss": 0.4503, | |
| "step": 125 | |
| }, | |
| { | |
| "epoch": 0.69, | |
| "learning_rate": 0.0002, | |
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| "step": 150 | |
| }, | |
| { | |
| "epoch": 0.81, | |
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| "step": 175 | |
| }, | |
| { | |
| "epoch": 0.93, | |
| "learning_rate": 0.0002, | |
| "loss": 0.2531, | |
| "step": 200 | |
| } | |
| ], | |
| "max_steps": 216, | |
| "num_train_epochs": 1, | |
| "total_flos": 7233885092118528.0, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |