Instructions to use OscarXZQ/tracking_shuffled_objects_seven_objects with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use OscarXZQ/tracking_shuffled_objects_seven_objects 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/tracking_shuffled_objects_seven_objects") - Notebooks
- Google Colab
- Kaggle
Download train_results.json from OscarXZQ/tracking_shuffled_objects_seven_objects: direct link, hf CLI and curl.
- Browser
- Download file 198 Bytes
-
https://huggingface.co/OscarXZQ/tracking_shuffled_objects_seven_objects/resolve/main/train_results.json
- Command line
-
hf download hf://OscarXZQ/tracking_shuffled_objects_seven_objects/train_results.json
-
curl -L -o train_results.json https://huggingface.co/OscarXZQ/tracking_shuffled_objects_seven_objects/resolve/main/train_results.json
198 Bytes
| { | |
| "epoch": 10.0, | |
| "total_flos": 292716416286720.0, | |
| "train_loss": 0.55819580078125, | |
| "train_runtime": 81.4415, | |
| "train_samples_per_second": 3.07, | |
| "train_steps_per_second": 3.07 | |
| } |