Fill-Mask
Transformers
PyTorch
English
babylm
babylm-2026
gpt-bert
sample-efficient-pretraining
muon
custom_code
Instructions to use svsatheesh/BabySteps_SidBert-100M-mixed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use svsatheesh/BabySteps_SidBert-100M-mixed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="svsatheesh/BabySteps_SidBert-100M-mixed", trust_remote_code=True)# Load model directly from transformers import GPTBERTFoCausalLM model = GPTBERTFoCausalLM.from_pretrained("svsatheesh/BabySteps_SidBert-100M-mixed", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff7a3c3c65223a223e2b1a571825a78892e6e07b72572d0c44995fa66baec6d8
- Size of remote file:
- 478 MB
- SHA256:
- c39481cb305c566a631737a38b48d70bee702b2613ba356756ef4bbb97ed175b
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