Instructions to use lleticiasilvaa/CodeS-1B-text2SQL-alias-indentacao with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lleticiasilvaa/CodeS-1B-text2SQL-alias-indentacao with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lleticiasilvaa/CodeS-1B-text2SQL-alias-indentacao", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.2333994631812347, | |
| "eval_steps": 250, | |
| "global_step": 250, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.2333994631812347, | |
| "grad_norm": 8.384697914123535, | |
| "learning_rate": 8.959847237666421e-05, | |
| "loss": 0.3776, | |
| "step": 250 | |
| }, | |
| { | |
| "epoch": 0.2333994631812347, | |
| "eval_loss": 0.2075573056936264, | |
| "eval_runtime": 14.5853, | |
| "eval_samples_per_second": 5.965, | |
| "eval_steps_per_second": 5.965, | |
| "step": 250 | |
| } | |
| ], | |
| "logging_steps": 250, | |
| "max_steps": 1071, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 1, | |
| "save_steps": 250, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": false | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 6785029677735936.0, | |
| "train_batch_size": 1, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |