Instructions to use ShengdingHu/sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShengdingHu/sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ShengdingHu/sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ShengdingHu/sst2") model = AutoModelForMaskedLM.from_pretrained("ShengdingHu/sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 3.0, | |
| "eval_accuracy": 0.5172018348623854, | |
| "eval_loss": 3.1630539894104004, | |
| "eval_runtime": 12.2812, | |
| "eval_samples": 872, | |
| "eval_samples_per_second": 71.003, | |
| "eval_steps_per_second": 8.875 | |
| } |