Instructions to use Jeevesh8/sMLM-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/sMLM-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Jeevesh8/sMLM-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/sMLM-bert") model = AutoModelForMaskedLM.from_pretrained("Jeevesh8/sMLM-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jeevesh8/sMLM-bert: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/Jeevesh8/sMLM-bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jeevesh8/sMLM-bert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jeevesh8/sMLM-bert/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- af38a164d61953b3acd9aa321be010a18cadb2c7f1ab3da73fcf5e4e33e59bff
- Size of remote file:
- 433 MB
- SHA256:
- c65cd64d61ecb253b52141446cd073d67b80be957fa3cf45c94dda3ee7ab060e
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