Instructions to use harish/PT-FalseFalse-0_2_BEST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/PT-FalseFalse-0_2_BEST with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harish/PT-FalseFalse-0_2_BEST")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harish/PT-FalseFalse-0_2_BEST") model = AutoModelForSequenceClassification.from_pretrained("harish/PT-FalseFalse-0_2_BEST", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download trainer_state.json from harish/PT-FalseFalse-0_2_BEST: direct link, hf CLI and curl.
- Browser
- Download file 622 Bytes
-
https://huggingface.co/harish/PT-FalseFalse-0_2_BEST/resolve/main/trainer_state.json
- Command line
-
hf download hf://harish/PT-FalseFalse-0_2_BEST/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/harish/PT-FalseFalse-0_2_BEST/resolve/main/trainer_state.json
622 Bytes
| { | |
| "best_metric": 0.694915235042572, | |
| "best_model_checkpoint": "OUTPUT/bert-base-multilingual-cased/FalseFalse-0/2/checkpoint-28", | |
| "epoch": 1.0, | |
| "global_step": 28, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 1.0, | |
| "eval_accuracy": 0.694915235042572, | |
| "eval_loss": 0.5861443281173706, | |
| "eval_runtime": 3.3566, | |
| "eval_samples_per_second": 70.309, | |
| "step": 28 | |
| } | |
| ], | |
| "max_steps": 252, | |
| "num_train_epochs": 9, | |
| "total_flos": 119245359969792.0, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |