Instructions to use Agra2002/finetuned_bertuncased_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Agra2002/finetuned_bertuncased_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Agra2002/finetuned_bertuncased_sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Agra2002/finetuned_bertuncased_sentiment") model = AutoModelForSequenceClassification.from_pretrained("Agra2002/finetuned_bertuncased_sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download test.csv from Agra2002/finetuned_bertuncased_sentiment: direct link, hf CLI and curl.
- Browser
- Download file 33.3 MB
-
https://huggingface.co/Agra2002/finetuned_bertuncased_sentiment/resolve/main/test.csv
- Command line
-
hf download hf://Agra2002/finetuned_bertuncased_sentiment/test.csv
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curl -L -o test.csv https://huggingface.co/Agra2002/finetuned_bertuncased_sentiment/resolve/main/test.csv
33.3 MB
- Xet hash:
- e1cf9b9111d3712e656d08f0d942a5a61293af79061cedd9d80004a0ce2ff129
- Size of remote file:
- 33.3 MB
- SHA256:
- b15cdae145ece4f0d2284fe4cc5da41093d779c0a5b08f868b5862e95972731d
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