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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.onnx from newmindai/Mursit-Base: direct link, hf CLI and curl.
- Browser
- Download file 626 MB
-
https://huggingface.co/newmindai/Mursit-Base/resolve/refs%2Fpr%2F1/model.onnx
- Command line
-
hf download hf://newmindai/Mursit-Base@refs/pr/1/model.onnx
-
curl -L -o model.onnx https://huggingface.co/newmindai/Mursit-Base/resolve/refs%2Fpr%2F1/model.onnx
626 MB
- Xet hash:
- dc00100d11c5b210f4d448cb9170540f129e415e5c5d90c4285d3a16d987b05f
- Size of remote file:
- 626 MB
- SHA256:
- d7cec3828bf4e48aec81927a5d2eee7dc2af0d4264b186a3c0c08d3c01885d41
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