Text Classification
Transformers
Safetensors
Serbian
roberta
serbian
sentiment-analysis
wordnet
sentiwordnet
lexicon-induction
text-embeddings-inference
Instructions to use Tanor/Jerteh355SENTNEG6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/Jerteh355SENTNEG6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/Jerteh355SENTNEG6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/Jerteh355SENTNEG6") model = AutoModelForSequenceClassification.from_pretrained("Tanor/Jerteh355SENTNEG6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Tanor/Jerteh355SENTNEG6: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/Tanor/Jerteh355SENTNEG6/resolve/main/training_args.bin
- Command line
-
hf download hf://Tanor/Jerteh355SENTNEG6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Tanor/Jerteh355SENTNEG6/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- b7860ca2eb7735c0f35a69e58f3ca5f47c0636b444baff647c7653dfed5255ee
- Size of remote file:
- 4.98 kB
- SHA256:
- 25e5b2ae90db724d0aded3221a6923fa34579981417c1f4c48cb5adac8c30993
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