Text Classification
Transformers
PyTorch
Serbian
gpt2
serbian
sentiment-analysis
wordnet
sentiwordnet
lexicon-induction
Instructions to use Tanor/SRGPTSENTPOS6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/SRGPTSENTPOS6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/SRGPTSENTPOS6")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/SRGPTSENTPOS6") model = AutoModelForSequenceClassification.from_pretrained("Tanor/SRGPTSENTPOS6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Tanor/SRGPTSENTPOS6: direct link, hf CLI and curl.
- Browser
- Download file 4.41 kB
-
https://huggingface.co/Tanor/SRGPTSENTPOS6/resolve/main/training_args.bin
- Command line
-
hf download hf://Tanor/SRGPTSENTPOS6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Tanor/SRGPTSENTPOS6/resolve/main/training_args.bin
4.41 kB
- Xet hash:
- b764acd253e477757d7086bb4156874e2319293997c01e6b582793178d6199c5
- Size of remote file:
- 4.41 kB
- SHA256:
- 070221335ba90a29b6b6d12d2b25006f6ea35f3f7949063ccfdb53b0499c3c55
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