Instructions to use OscarXZQ/boolean_expressions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use OscarXZQ/boolean_expressions with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large") model = PeftModel.from_pretrained(base_model, "OscarXZQ/boolean_expressions") - Notebooks
- Google Colab
- Kaggle
Download trainer_state.json from OscarXZQ/boolean_expressions: direct link, hf CLI and curl.
- Browser
- Download file 985 Bytes
-
https://huggingface.co/OscarXZQ/boolean_expressions/resolve/main/trainer_state.json
- Command line
-
hf download hf://OscarXZQ/boolean_expressions/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/OscarXZQ/boolean_expressions/resolve/main/trainer_state.json
985 Bytes
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 10.0, | |
| "eval_steps": 500, | |
| "global_step": 250, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 10.0, | |
| "step": 250, | |
| "total_flos": 36510280335360.0, | |
| "train_loss": 0.29100747680664063, | |
| "train_runtime": 79.5142, | |
| "train_samples_per_second": 3.144, | |
| "train_steps_per_second": 3.144 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 250, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 10, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 36510280335360.0, | |
| "train_batch_size": 1, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |