Instructions to use tybritten/lora-for-starcoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tybritten/lora-for-starcoder with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/tmp/model") model = PeftModel.from_pretrained(base_model, "tybritten/lora-for-starcoder") - Notebooks
- Google Colab
- Kaggle
File size: 703 Bytes
d73ad11 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | {
"best_metric": 1.6104975938796997,
"best_model_checkpoint": "./outputdir/checkpoint-10",
"epoch": 1.0,
"global_step": 10,
"is_hyper_param_search": false,
"is_local_process_zero": true,
"is_world_process_zero": true,
"log_history": [
{
"epoch": 1.0,
"learning_rate": 0.0,
"loss": 1.6036,
"step": 10
},
{
"epoch": 1.0,
"eval_loss": 1.6104975938796997,
"eval_runtime": 2007.0049,
"eval_samples_per_second": 1.466,
"eval_steps_per_second": 1.466,
"step": 10
}
],
"max_steps": 10,
"num_train_epochs": 9223372036854775807,
"total_flos": 2.988576972000461e+16,
"trial_name": null,
"trial_params": null
}
|