Instructions to use vaibhav9/bert_uncased_L-4_H-256_A-4-finetuned-hangman with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vaibhav9/bert_uncased_L-4_H-256_A-4-finetuned-hangman with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="vaibhav9/bert_uncased_L-4_H-256_A-4-finetuned-hangman")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("vaibhav9/bert_uncased_L-4_H-256_A-4-finetuned-hangman") model = AutoModelForMaskedLM.from_pretrained("vaibhav9/bert_uncased_L-4_H-256_A-4-finetuned-hangman", device_map="auto") - Notebooks
- Google Colab
- Kaggle