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 train.csv from Agra2002/finetuned_bertuncased_sentiment: direct link, hf CLI and curl.
- Browser
- Download file 32.6 MB
-
https://huggingface.co/Agra2002/finetuned_bertuncased_sentiment/resolve/main/train.csv
- Command line
-
hf download hf://Agra2002/finetuned_bertuncased_sentiment/train.csv
-
curl -L -o train.csv https://huggingface.co/Agra2002/finetuned_bertuncased_sentiment/resolve/main/train.csv
32.6 MB
- Xet hash:
- 8c33e83ee00ccb0fd89a0b15a785936dfb3434451c60303d10954af0baf9c177
- Size of remote file:
- 32.6 MB
- SHA256:
- d684ff5d05ab1b6c5ce7a865ae771d376e42dffaa28c867e9bbc80a95b1c80da
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