Instructions to use kwang123/bert-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kwang123/bert-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kwang123/bert-sentiment-analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kwang123/bert-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("kwang123/bert-sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kwang123/bert-sentiment-analysis: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/kwang123/bert-sentiment-analysis/resolve/main/training_args.bin
- Command line
-
hf download hf://kwang123/bert-sentiment-analysis/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/kwang123/bert-sentiment-analysis/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 69ef031d3841a79c25e955d0255438b67f12b6426161b70a852784c45a49d645
- Size of remote file:
- 4.54 kB
- SHA256:
- 991a285ce10995c48c56713dbbba5f90190b3c2dcdba53b5fbeeb8d2b56109e0
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