Instructions to use abanoub1412/finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abanoub1412/finetuning with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("abanoub1412/finetuning") model = AutoModelForSeq2SeqLM.from_pretrained("abanoub1412/finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download trainer_state.json from abanoub1412/finetuning: direct link, hf CLI and curl.
- Browser
- Download file 467 Bytes
-
https://huggingface.co/abanoub1412/finetuning/resolve/main/trainer_state.json
- Command line
-
hf download hf://abanoub1412/finetuning/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/abanoub1412/finetuning/resolve/main/trainer_state.json
467 Bytes
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 3.0, | |
| "global_step": 60, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 3.0, | |
| "step": 60, | |
| "train_runtime": 1377.3776, | |
| "train_samples_per_second": 0.044 | |
| } | |
| ], | |
| "max_steps": 60, | |
| "num_train_epochs": 3, | |
| "total_flos": 124544815294464, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |