Instructions to use DGurgurov/mbert_npi-deva with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DGurgurov/mbert_npi-deva with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="DGurgurov/mbert_npi-deva")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("DGurgurov/mbert_npi-deva") model = AutoModelForMaskedLM.from_pretrained("DGurgurov/mbert_npi-deva", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from DGurgurov/mbert_npi-deva: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/DGurgurov/mbert_npi-deva/resolve/main/optimizer.pt
- Command line
-
hf download hf://DGurgurov/mbert_npi-deva/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/DGurgurov/mbert_npi-deva/resolve/main/optimizer.pt
1.42 GB
- Xet hash:
- 4a41b0afeb2f19509e4a72464519857fa993abf2b416c551ea45c0c4bda52657
- Size of remote file:
- 1.42 GB
- SHA256:
- ee0e6efe7350ebd6cc4f26ede311547643b6baed0c7af14930c2fb406181be9e
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