Instructions to use Syzseisus/LCK_LLM5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Syzseisus/LCK_LLM5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("vaiv/GeM2-Llamion-14B-Chat") model = PeftModel.from_pretrained(base_model, "Syzseisus/LCK_LLM5") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.013247665099026296, | |
| "eval_steps": 500, | |
| "global_step": 800, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.001655958137378287, | |
| "grad_norm": 0.19597935676574707, | |
| "learning_rate": 0.00019966890756553004, | |
| "loss": 2.1972, | |
| "step": 100 | |
| }, | |
| { | |
| "epoch": 0.003311916274756574, | |
| "grad_norm": 0.25808241963386536, | |
| "learning_rate": 0.00019933771577352244, | |
| "loss": 1.9677, | |
| "step": 200 | |
| }, | |
| { | |
| "epoch": 0.0049678744121348616, | |
| "grad_norm": 0.23811133205890656, | |
| "learning_rate": 0.00019900652398151486, | |
| "loss": 1.9341, | |
| "step": 300 | |
| }, | |
| { | |
| "epoch": 0.006623832549513148, | |
| "grad_norm": 0.26714324951171875, | |
| "learning_rate": 0.00019867533218950728, | |
| "loss": 1.915, | |
| "step": 400 | |
| }, | |
| { | |
| "epoch": 0.008279790686891435, | |
| "grad_norm": 0.23645658791065216, | |
| "learning_rate": 0.0001983441403974997, | |
| "loss": 1.8916, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 0.009935748824269723, | |
| "grad_norm": 0.2878512740135193, | |
| "learning_rate": 0.00019801294860549213, | |
| "loss": 1.9003, | |
| "step": 600 | |
| }, | |
| { | |
| "epoch": 0.01159170696164801, | |
| "grad_norm": 0.2687942087650299, | |
| "learning_rate": 0.00019768175681348456, | |
| "loss": 1.876, | |
| "step": 700 | |
| }, | |
| { | |
| "epoch": 0.013247665099026296, | |
| "grad_norm": 0.2722982168197632, | |
| "learning_rate": 0.00019735056502147698, | |
| "loss": 1.9004, | |
| "step": 800 | |
| } | |
| ], | |
| "logging_steps": 100, | |
| "max_steps": 60388, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 1, | |
| "save_steps": 800, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": false | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 5.53158703054848e+17, | |
| "train_batch_size": 16, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |