Instructions to use Cheng98/opt-125m-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cheng98/opt-125m-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cheng98/opt-125m-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cheng98/opt-125m-mnli") model = AutoModelForSequenceClassification.from_pretrained("Cheng98/opt-125m-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 5.0, | |
| "epoch_mm": 5.0, | |
| "eval_accuracy": 0.8208863983698421, | |
| "eval_accuracy_mm": 0.8217046379170057, | |
| "eval_loss": 1.2960911989212036, | |
| "eval_loss_mm": 1.273514986038208, | |
| "eval_runtime": 13.5254, | |
| "eval_runtime_mm": 13.4557, | |
| "eval_samples": 9815, | |
| "eval_samples_mm": 9832, | |
| "eval_samples_per_second": 725.672, | |
| "eval_samples_per_second_mm": 730.694, | |
| "eval_steps_per_second": 90.718, | |
| "eval_steps_per_second_mm": 91.337 | |
| } |