Text Classification
Transformers
PyTorch
Safetensors
Serbian
electra
serbian
sentiment-analysis
wordnet
sentiwordnet
lexicon-induction
Instructions to use Tanor/BERTicSENTPOS6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/BERTicSENTPOS6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/BERTicSENTPOS6")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/BERTicSENTPOS6") model = AutoModelForSequenceClassification.from_pretrained("Tanor/BERTicSENTPOS6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Tanor/BERTicSENTPOS6: direct link, hf CLI and curl.
- Browser
- Download file 734 kB
-
https://huggingface.co/Tanor/BERTicSENTPOS6/resolve/main/tokenizer.json
- Command line
-
hf download hf://Tanor/BERTicSENTPOS6/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Tanor/BERTicSENTPOS6/resolve/main/tokenizer.json
734 kB
File too large to display, you can check the raw version instead.