Instructions to use sumitrsch/muril_large_multiconer22_bn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumitrsch/muril_large_multiconer22_bn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sumitrsch/muril_large_multiconer22_bn")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sumitrsch/muril_large_multiconer22_bn") model = AutoModelForTokenClassification.from_pretrained("sumitrsch/muril_large_multiconer22_bn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download bn_test.csv from sumitrsch/muril_large_multiconer22_bn: direct link, hf CLI and curl.
- Browser
- Download file 18.3 MB
-
https://huggingface.co/sumitrsch/muril_large_multiconer22_bn/resolve/main/bn_test.csv
- Command line
-
hf download hf://sumitrsch/muril_large_multiconer22_bn/bn_test.csv
-
curl -L -o bn_test.csv https://huggingface.co/sumitrsch/muril_large_multiconer22_bn/resolve/main/bn_test.csv
18.3 MB
- Xet hash:
- cfa1a0a268750857b31014b96ac5a55cc6429c165125b5ef2ba01d19f894956f
- Size of remote file:
- 18.3 MB
- SHA256:
- a1a624343c0525fd0b0d753a06d458244cf1b95ec0594ade7d9e4ff2f9eba459
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