Text Classification
Transformers
PyTorch
Korean
xlm-roberta
XLM-RoBERTa
KorFin-ASC
financial-sentiment-analysis
sentiment-analysis
text-embeddings-inference
Instructions to use amphora/KorFinASC-XLM-RoBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amphora/KorFinASC-XLM-RoBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amphora/KorFinASC-XLM-RoBERTa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amphora/KorFinASC-XLM-RoBERTa") model = AutoModelForSequenceClassification.from_pretrained("amphora/KorFinASC-XLM-RoBERTa") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened about 3 years ago
by
SFconvertbot