Instructions to use SRDdev/MaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SRDdev/MaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SRDdev/MaskedLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SRDdev/MaskedLM") model = AutoModelForMaskedLM.from_pretrained("SRDdev/MaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (6aaf81963946be454a5f10d9174b6324f0ef3a88) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>c73d3b1
-
Update README.md
908c247 -
Update README.md
1fece1b -
v3
da96646 -
v3
bc2f61e -
Update README.md
c113a01
-
v2
64923ff -
v2
36ea65b -
Version 1
3809924 -
Version 1
6bae6f5 -
Update README.md
7ab934c -
Create README.md
a9f81e5 -
End of Training
2dff944 -
initial commit
4b489d6