Instructions to use ShinDC/distilbert-base-cased-finetuned-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShinDC/distilbert-base-cased-finetuned-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ShinDC/distilbert-base-cased-finetuned-imdb")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ShinDC/distilbert-base-cased-finetuned-imdb") model = AutoModelForMaskedLM.from_pretrained("ShinDC/distilbert-base-cased-finetuned-imdb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 727fea2f10b8d6582b7d77280f5598713d8cc39f034a775791b61e929d39f2e8
- Size of remote file:
- 263 MB
- SHA256:
- ffc8d2d260f91910eed23059c9e8802d2c0c992502934b0ab1919306777f9d8f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.