Instructions to use Souvikcmsa/SentimentAnalysisDistillBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Souvikcmsa/SentimentAnalysisDistillBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Souvikcmsa/SentimentAnalysisDistillBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Souvikcmsa/SentimentAnalysisDistillBERT") model = AutoModelForSequenceClassification.from_pretrained("Souvikcmsa/SentimentAnalysisDistillBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download sample_input.pkl from Souvikcmsa/SentimentAnalysisDistillBERT: direct link, hf CLI and curl.
- Browser
- Download file 2.03 kB
-
https://huggingface.co/Souvikcmsa/SentimentAnalysisDistillBERT/resolve/main/sample_input.pkl
- Command line
-
hf download hf://Souvikcmsa/SentimentAnalysisDistillBERT/sample_input.pkl
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curl -L -o sample_input.pkl https://huggingface.co/Souvikcmsa/SentimentAnalysisDistillBERT/resolve/main/sample_input.pkl
2.03 kB
- Xet hash:
- 77eae12518b4e7f8eeb6165115be5285f04a47b9343cee92f368ef268e28c76a
- Size of remote file:
- 2.03 kB
- SHA256:
- 7be1cb1a33be8f6706bcda5b518f20917427f2459c8b5079e06268b5900a81b1
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