Instructions to use nhrony/bert-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nhrony/bert-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nhrony/bert-final")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nhrony/bert-final") model = AutoModelForMaskedLM.from_pretrained("nhrony/bert-final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nhrony/bert-final: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/nhrony/bert-final/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nhrony/bert-final/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nhrony/bert-final/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 91c6b2fb24e2dc2967be80b7abb2e8bca1effbd96ded8df97301d7e86b940288
- Size of remote file:
- 268 MB
- SHA256:
- 589ffef55433dbe84f1b304c76fdb4647ac201ec66b19928875ebfcaf5afa9c5
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