Text Classification
Transformers
PyTorch
Serbian
gpt2
serbian
sentiment-analysis
wordnet
sentiwordnet
lexicon-induction
Instructions to use Tanor/SRGPTSENTNEG0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/SRGPTSENTNEG0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/SRGPTSENTNEG0")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/SRGPTSENTNEG0") model = AutoModelForSequenceClassification.from_pretrained("Tanor/SRGPTSENTNEG0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Tanor/SRGPTSENTNEG0: direct link, hf CLI and curl.
- Browser
- Download file 4.41 kB
-
https://huggingface.co/Tanor/SRGPTSENTNEG0/resolve/main/training_args.bin
- Command line
-
hf download hf://Tanor/SRGPTSENTNEG0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Tanor/SRGPTSENTNEG0/resolve/main/training_args.bin
4.41 kB
- Xet hash:
- f2405fd6d42c12ada9e6b0e141122f28f01c41e14dffadcba47ffe6eec4630c0
- Size of remote file:
- 4.41 kB
- SHA256:
- c4f7a50597e0dd1369d13fd237aede9ed7677e2ece2618c11712cc40775bea0a
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