Instructions to use robzchhangte/MizBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use robzchhangte/MizBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="robzchhangte/MizBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("robzchhangte/MizBERT") model = AutoModelForMaskedLM.from_pretrained("robzchhangte/MizBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from robzchhangte/MizBERT: direct link, hf CLI and curl.
- Browser
- Download file 876 MB
-
https://huggingface.co/robzchhangte/MizBERT/resolve/main/optimizer.pt
- Command line
-
hf download hf://robzchhangte/MizBERT/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/robzchhangte/MizBERT/resolve/main/optimizer.pt
876 MB
- Xet hash:
- 5c26552dde4230c23450ae41eefbe37795b941b9df286b9059487f9eb118ad02
- Size of remote file:
- 876 MB
- SHA256:
- 7f06a611c8f461963216b0292b39a3f96da2c555134e894145e276f69c3cad3a
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