Instructions to use paul21/llama-30b-20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use paul21/llama-30b-20 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/gpfsscratch/rech/cwa/umm59ig/llm/llama-30b") model = PeftModel.from_pretrained(base_model, "paul21/llama-30b-20") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.02, | |
| "global_step": 20, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.01, | |
| "learning_rate": 1e-05, | |
| "loss": 1.8152, | |
| "step": 10 | |
| }, | |
| { | |
| "epoch": 0.01, | |
| "eval_loss": 1.8217052221298218, | |
| "eval_runtime": 3139.8873, | |
| "eval_samples_per_second": 0.105, | |
| "eval_steps_per_second": 0.105, | |
| "step": 10 | |
| }, | |
| { | |
| "epoch": 0.02, | |
| "learning_rate": 2e-05, | |
| "loss": 1.8212, | |
| "step": 20 | |
| }, | |
| { | |
| "epoch": 0.02, | |
| "eval_loss": 1.8069214820861816, | |
| "eval_runtime": 3158.5963, | |
| "eval_samples_per_second": 0.104, | |
| "eval_steps_per_second": 0.104, | |
| "step": 20 | |
| } | |
| ], | |
| "max_steps": 1000, | |
| "num_train_epochs": 9223372036854775807, | |
| "total_flos": 1.282136815477719e+17, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |