Instructions to use Intel/xlnet-base-cased-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/xlnet-base-cased-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Intel/xlnet-base-cased-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Intel/xlnet-base-cased-mrpc") model = AutoModelForSequenceClassification.from_pretrained("Intel/xlnet-base-cased-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 193 Bytes
686aebc | 1 2 3 4 5 6 7 8 | {
"epoch": 5.0,
"train_loss": 0.2684407242484715,
"train_runtime": 5649.8451,
"train_samples": 3668,
"train_samples_per_second": 3.246,
"train_steps_per_second": 0.204
} |