Feature Extraction
Transformers
PyTorch
ONNX
Safetensors
Turkish
English
modernbert
fill-mask
turkish
legal
turkish-legal
mecellem
TRUBA
MN5
text-embeddings-inference
Instructions to use newmindai/Mursit-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use newmindai/Mursit-Large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="newmindai/Mursit-Large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("newmindai/Mursit-Large") model = AutoModelForMaskedLM.from_pretrained("newmindai/Mursit-Large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3f9c491b7303e92bd51a685b127de7a8c31a5faa272f8ea004d2ace1f076d78
- Size of remote file:
- 1.62 GB
- SHA256:
- 276f10308ec4c7fc5a54c1df036d0bf65f36bd20fab2d29d0c5f5412ccd2b717
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