Instructions to use Vishwas1/bert-base-imdb2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vishwas1/bert-base-imdb2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Vishwas1/bert-base-imdb2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Vishwas1/bert-base-imdb2") model = AutoModelForSequenceClassification.from_pretrained("Vishwas1/bert-base-imdb2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Vishwas1/bert-base-imdb2: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/Vishwas1/bert-base-imdb2/resolve/main/training_args.bin
- Command line
-
hf download hf://Vishwas1/bert-base-imdb2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Vishwas1/bert-base-imdb2/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 6f2bed24301bf719f77ddf22ba65ed57b3dcfc06ca961e4bc757f2af26a88836
- Size of remote file:
- 5.18 kB
- SHA256:
- 07c385f60328e9f12cc44452bed4086ab9756368d180ace72ebbe385c7b66d2f
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