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:
- 4ee441f838417c452f9bf00218f129e62863ed3ee243283fc0875ecb2e886684
- Size of remote file:
- 4.54 kB
- SHA256:
- c67bb15935802620a383ad654b4397417bbc9096273f652dddb313607b5e3d6b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.