Instructions to use Vishwas1/bert-base-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vishwas1/bert-base-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Vishwas1/bert-base-imdb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Vishwas1/bert-base-imdb") model = AutoModelForSequenceClassification.from_pretrained("Vishwas1/bert-base-imdb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Vishwas1/bert-base-imdb: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/Vishwas1/bert-base-imdb/resolve/main/training_args.bin
- Command line
-
hf download hf://Vishwas1/bert-base-imdb/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Vishwas1/bert-base-imdb/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- e270d08b16e8651fb393b40384792e7fe32a7915db15e6881e7f3ae8368fc3ce
- Size of remote file:
- 5.18 kB
- SHA256:
- def19f40e5b5aa8f76f1cda13caf8a2af2d285b453b48b7d8ac1f5128770a918
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