Text Classification
Transformers
PyTorch
Serbian
gpt2
serbian
sentiment-analysis
wordnet
sentiwordnet
lexicon-induction
Instructions to use Tanor/SRGPTSENTPOS2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/SRGPTSENTPOS2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/SRGPTSENTPOS2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/SRGPTSENTPOS2") model = AutoModelForSequenceClassification.from_pretrained("Tanor/SRGPTSENTPOS2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Tanor/SRGPTSENTPOS2: direct link, hf CLI and curl.
- Browser
- Download file 4.41 kB
-
https://huggingface.co/Tanor/SRGPTSENTPOS2/resolve/19c69b9f547b2de51a0e282b1fc9d031c0cc51ce/training_args.bin
- Command line
-
hf download hf://Tanor/SRGPTSENTPOS2@19c69b9f547b2de51a0e282b1fc9d031c0cc51ce/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Tanor/SRGPTSENTPOS2/resolve/19c69b9f547b2de51a0e282b1fc9d031c0cc51ce/training_args.bin
4.41 kB
- Xet hash:
- a4b382c3db09735e1ed98811f492fa3313f9d80040f0c2ec703a282869e33e7b
- Size of remote file:
- 4.41 kB
- SHA256:
- 9b556bea45dcaf6bcff4c686b1247635bc732b3cd5f72c9aa43d1e8d9b378837
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