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 sample_input.pkl from Souvikcmsa/BERT_sentiment_analysis: direct link, hf CLI and curl.
- Browser
- Download file 2.85 kB
-
https://huggingface.co/Souvikcmsa/BERT_sentiment_analysis/resolve/main/sample_input.pkl
- Command line
-
hf download hf://Souvikcmsa/BERT_sentiment_analysis/sample_input.pkl
-
curl -L -o sample_input.pkl https://huggingface.co/Souvikcmsa/BERT_sentiment_analysis/resolve/main/sample_input.pkl
2.85 kB
- Xet hash:
- a27363f35d3f62a247422bd85e6a11d4d4cd3dfa112a3e7bfd2d89633c2cb4eb
- Size of remote file:
- 2.85 kB
- SHA256:
- 3b4aea8ee080351fdae9509a2b90a9c4dd6a57464acc1f84fc6dcd60201ac7ce
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