Text Classification
Transformers
Safetensors
Serbian
roberta
serbian
sentiment-analysis
wordnet
sentiwordnet
lexicon-induction
text-embeddings-inference
Instructions to use Tanor/Jerteh355SENTPOS4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/Jerteh355SENTPOS4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/Jerteh355SENTPOS4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/Jerteh355SENTPOS4") model = AutoModelForSequenceClassification.from_pretrained("Tanor/Jerteh355SENTPOS4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Tanor/Jerteh355SENTPOS4: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/Tanor/Jerteh355SENTPOS4/resolve/main/training_args.bin
- Command line
-
hf download hf://Tanor/Jerteh355SENTPOS4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Tanor/Jerteh355SENTPOS4/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- be18dd421a89032212f2c633b9af61e7fcc05920406dc15c5593453249cdb313
- Size of remote file:
- 4.98 kB
- SHA256:
- 085d546616fa6cbb462e24e856fe017a38f1baff425b89bb473643a91aee1544
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