Instructions to use Xenserv/NepaliSentimentAnalysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Xenserv/NepaliSentimentAnalysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Xenserv/NepaliSentimentAnalysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Xenserv/NepaliSentimentAnalysis") model = AutoModelForSequenceClassification.from_pretrained("Xenserv/NepaliSentimentAnalysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
731c7f0 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:18f0fc93b206b8a1ddd8063cb29bb1f56e0fda4c6acfead803640582af243860
size 5240
|