Instructions to use google/muril-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/muril-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google/muril-base-cased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google/muril-base-cased") model = AutoModelForMaskedLM.from_pretrained("google/muril-base-cased", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model
f7203dd
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Max length = 512 (#2)
- Max length = 512 (cd9f19a1404d9ae6a0b39570f6084c94d742c5db) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>afd9f36
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upload flax model
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allow flax
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Create README.md
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adding model files
Simran Khanuja49973d4
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initial commit
68c4088