Instructions to use Souvikcmsa/BERT_sentiment_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Souvikcmsa/BERT_sentiment_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Souvikcmsa/BERT_sentiment_analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Souvikcmsa/BERT_sentiment_analysis") model = AutoModelForSequenceClassification.from_pretrained("Souvikcmsa/BERT_sentiment_analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Souvikcmsa/BERT_sentiment_analysis: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Souvikcmsa/BERT_sentiment_analysis/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Souvikcmsa/BERT_sentiment_analysis/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Souvikcmsa/BERT_sentiment_analysis/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 0e4d2c7f40fef70c57c91cc3b9742986d39cecd297aad7072ecf5595f2e523a0
- Size of remote file:
- 438 MB
- SHA256:
- d4ee83e207cd138b63600f23ca3086e2c73da4ec726274a71d768f838450df33
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