Instructions to use TirthDesai/IMDB-Reviews-Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TirthDesai/IMDB-Reviews-Analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TirthDesai/IMDB-Reviews-Analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TirthDesai/IMDB-Reviews-Analysis") model = AutoModelForSequenceClassification.from_pretrained("TirthDesai/IMDB-Reviews-Analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from TirthDesai/IMDB-Reviews-Analysis: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/TirthDesai/IMDB-Reviews-Analysis/resolve/main/tokenizer.json
- Command line
-
hf download hf://TirthDesai/IMDB-Reviews-Analysis/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/TirthDesai/IMDB-Reviews-Analysis/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- e658c529e16f6cd24ed4a43f0031c4fef528916abe5451b7a7cde9dee9300e11
- Size of remote file:
- 17.2 MB
- SHA256:
- 934b17a59dcf1077002194f8f96b50ba2e6f1ac7f2ee2457dc73a7d92ac47a75
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