Instructions to use adalbertojunior/clip-rpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adalbertojunior/clip-rpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="adalbertojunior/clip-rpt")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("adalbertojunior/clip-rpt") model = AutoModel.from_pretrained("adalbertojunior/clip-rpt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 3.0, | |
| "global_step": 291, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 3.0, | |
| "step": 291, | |
| "total_flos": 9857580782400000.0, | |
| "train_loss": 1.5387164243717784, | |
| "train_runtime": 5043.8105, | |
| "train_samples_per_second": 14.638, | |
| "train_steps_per_second": 0.058 | |
| } | |
| ], | |
| "max_steps": 291, | |
| "num_train_epochs": 3, | |
| "total_flos": 9857580782400000.0, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |