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")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google/muril-base-cased") model = AutoModelForMaskedLM.from_pretrained("google/muril-base-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
Upload tokenizer.json
#5 opened 8 months ago
by
InvincibleSloth
add supported languages to metadata
#4 opened almost 2 years ago
by
hamzas
Adding `safetensors` variant of this model
#3 opened about 3 years ago
by
SFconvertbot
model_max_length effectively infinite
6
#1 opened almost 4 years ago
by
AngledLuffa