Instructions to use Sumedhzz/Sentiment-Analyzer-Quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sumedhzz/Sentiment-Analyzer-Quantized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sumedhzz/Sentiment-Analyzer-Quantized")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sumedhzz/Sentiment-Analyzer-Quantized") model = AutoModelForSequenceClassification.from_pretrained("Sumedhzz/Sentiment-Analyzer-Quantized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Sumedhzz/Sentiment-Analyzer-Quantized: direct link, hf CLI and curl.
- Browser
- Download file 16.8 MB
-
https://huggingface.co/Sumedhzz/Sentiment-Analyzer-Quantized/resolve/main/tokenizer.json
- Command line
-
hf download hf://Sumedhzz/Sentiment-Analyzer-Quantized/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Sumedhzz/Sentiment-Analyzer-Quantized/resolve/main/tokenizer.json
16.8 MB
- Xet hash:
- 05e0eee3eb15165e9c3a18f4d7b06e1a4d5fc704091f149e70e6d94abdfeebf6
- Size of remote file:
- 16.8 MB
- SHA256:
- ba7ba696dcec1db50526d3643ab6c496f28977ec60217f2a3d1388d6250cd0a6
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