Instructions to use Jeevesh8/DA-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/DA-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Jeevesh8/DA-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/DA-bert") model = AutoModelForMaskedLM.from_pretrained("Jeevesh8/DA-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jeevesh8/DA-bert: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/Jeevesh8/DA-bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jeevesh8/DA-bert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jeevesh8/DA-bert/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 49ce877373570f4cd2070cf673425938d88448e6472a11d76b5861f5e150b50b
- Size of remote file:
- 433 MB
- SHA256:
- d3f661cd9aa21b3d3457c88eb67c2a25493ee06b3346d72968dc049f0dbcf4e7
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