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 pytorch_model.bin from Tanor/SRGPTSENTPOS6: direct link, hf CLI and curl.
- Browser
- Download file 3.09 GB
-
https://huggingface.co/Tanor/SRGPTSENTPOS6/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Tanor/SRGPTSENTPOS6/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Tanor/SRGPTSENTPOS6/resolve/main/pytorch_model.bin
3.09 GB
- Xet hash:
- e7ad8bfc351e14f46a862998535d2ef3c12514855b58da75cec11c063da0b0e8
- Size of remote file:
- 3.09 GB
- SHA256:
- 14f86751f8fc7ba6f3ad4efd5d0f621aaa5632fbf92232ee5501cdee2d6d645e
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