Text Classification
Transformers
PyTorch
Serbian
gpt2
serbian
sentiment-analysis
wordnet
sentiwordnet
lexicon-induction
Instructions to use Tanor/SRGPTSENTNEG6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/SRGPTSENTNEG6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/SRGPTSENTNEG6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/SRGPTSENTNEG6") model = AutoModelForSequenceClassification.from_pretrained("Tanor/SRGPTSENTNEG6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Tanor/SRGPTSENTNEG6: direct link, hf CLI and curl.
- Browser
- Download file 4.41 kB
-
https://huggingface.co/Tanor/SRGPTSENTNEG6/resolve/main/training_args.bin
- Command line
-
hf download hf://Tanor/SRGPTSENTNEG6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Tanor/SRGPTSENTNEG6/resolve/main/training_args.bin
4.41 kB
- Xet hash:
- 7b84b3e3211a0266b88ebe06f2417d2cc34085a690e5c3479c485c75f14d075c
- Size of remote file:
- 4.41 kB
- SHA256:
- e00463bc73d74105e915a6aaaa7937072ec0d5114250dc3d303a803ddf3e2ea0
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