Instructions to use blockenters/bert-based-uncased-imdb2-v01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blockenters/bert-based-uncased-imdb2-v01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="blockenters/bert-based-uncased-imdb2-v01")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("blockenters/bert-based-uncased-imdb2-v01") model = AutoModelForSequenceClassification.from_pretrained("blockenters/bert-based-uncased-imdb2-v01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from blockenters/bert-based-uncased-imdb2-v01: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/blockenters/bert-based-uncased-imdb2-v01/resolve/main/tokenizer.json
- Command line
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hf download hf://blockenters/bert-based-uncased-imdb2-v01/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/blockenters/bert-based-uncased-imdb2-v01/resolve/main/tokenizer.json
712 kB
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