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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
ea59bb0
1
Parent(s): abf064d
Adding `safetensors` variant of this model
Browse files- model.safetensors +3 -0
model.safetensors
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oid sha256:120e8eb7261e34a35109f216ec13272e75cea80d5a4d4bf5bb0ba214373db9ec
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size 2239631074
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