Instructions to use Learner-sai/muril-ner-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Learner-sai/muril-ner-multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Learner-sai/muril-ner-multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Learner-sai/muril-ner-multilingual") model = AutoModelForTokenClassification.from_pretrained("Learner-sai/muril-ner-multilingual", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b01324a2aa2f5dec313971f3c231b2b448db287e51128e9ad6566f404c58d02a
- Size of remote file:
- 5.27 kB
- SHA256:
- f1a7bc8c56b9eb2a0f09eb42579f7fe76f70af1418e59b8d2e9376ea8eb012f3
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