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-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use newmindai/Mursit-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="newmindai/Mursit-Base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("newmindai/Mursit-Base") model = AutoModelForMaskedLM.from_pretrained("newmindai/Mursit-Base") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- de62d1d90ac618ff6a790a03d579f57024fd55420a42a6be1b472d0ff49c8277
- Size of remote file:
- 156 kB
- SHA256:
- 35d74a68a424786e7eca5fe891553cb3a1cd162e9a972f3e0ab3a125e9280137
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