Instructions to use averageandyyy/distilbert-base-uncased-finetuned-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use averageandyyy/distilbert-base-uncased-finetuned-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="averageandyyy/distilbert-base-uncased-finetuned-imdb")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("averageandyyy/distilbert-base-uncased-finetuned-imdb") model = AutoModelForMaskedLM.from_pretrained("averageandyyy/distilbert-base-uncased-finetuned-imdb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from averageandyyy/distilbert-base-uncased-finetuned-imdb: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/averageandyyy/distilbert-base-uncased-finetuned-imdb/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://averageandyyy/distilbert-base-uncased-finetuned-imdb/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/averageandyyy/distilbert-base-uncased-finetuned-imdb/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- bde8e4c5b62a21d3bc289c280a42cd59a44cd35e8be4b28eb12b5d954f961e99
- Size of remote file:
- 268 MB
- SHA256:
- 9b8a1a1c9eb47c8628735b087e6ffa74e1814f383370cf137697ae7d5555a89b
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