# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("sumitrsch/multiconer2_muril_large_bn")
model = AutoModelForTokenClassification.from_pretrained("sumitrsch/multiconer2_muril_large_bn")Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
For prediction on test data use this link. https://colab.research.google.com/drive/1K-ED0yvMsdciNo52rluauQBEAg-DBomC?usp=sharing update best_model_path = "sumitrsch/multiconer2_muril_large_bn"
If you are using this code, cite paper "silp_nlp at SemEval-2023 Task 2: Cross-lingual Knowledge Transfer for Mono-lingual Learning" https://aclanthology.org/2023.semeval-1.164
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sumitrsch/multiconer2_muril_large_bn")