Text Classification
Transformers
Safetensors
Indonesian
English
xlm-roberta
sentiment-analysis
indonesian
multilingual
social-media
text-embeddings-inference
Instructions to use nahiar/sentiment-analysis-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nahiar/sentiment-analysis-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nahiar/sentiment-analysis-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nahiar/sentiment-analysis-v2") model = AutoModelForSequenceClassification.from_pretrained("nahiar/sentiment-analysis-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e36ae76bb6bf7c9fd209e929274db6e012a573db28ac39a339caaa648d29dcad
- Size of remote file:
- 5.84 kB
- SHA256:
- 228ed42715c963d674baf6116246ef1eb14a01f711a10c3c7682a24cc31b1141
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