Instructions to use Learner-sai/muril-ner-multilingual-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Learner-sai/muril-ner-multilingual-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Learner-sai/muril-ner-multilingual-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Learner-sai/muril-ner-multilingual-v2") model = AutoModelForTokenClassification.from_pretrained("Learner-sai/muril-ner-multilingual-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbbb5cc07713609e3678edc7c63ff8bce1844abffac6b34ec1197918d7e385a5
- Size of remote file:
- 5.2 kB
- SHA256:
- 0a22e9bfd14336042f366e5c511aa20bfb8991f43fbb510b432050f1afbe32c2
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