Instructions to use at2507/distilbert-base-uncased-finetuned-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use at2507/distilbert-base-uncased-finetuned-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="at2507/distilbert-base-uncased-finetuned-imdb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("at2507/distilbert-base-uncased-finetuned-imdb") model = AutoModelForMaskedLM.from_pretrained("at2507/distilbert-base-uncased-finetuned-imdb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from at2507/distilbert-base-uncased-finetuned-imdb: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/at2507/distilbert-base-uncased-finetuned-imdb/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://at2507/distilbert-base-uncased-finetuned-imdb/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/at2507/distilbert-base-uncased-finetuned-imdb/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 7b3e69aed884c8f12255cdc3e1724fa5db9b62332165c36b67a810b193f85d9d
- Size of remote file:
- 268 MB
- SHA256:
- a4d17e18d6259499fbb323903788208b88d8175e2bb445b828858f034b4aa464
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