Fill-Mask
Transformers
Safetensors
English
lewis_44m_bert
bert
encoder
masked-lm
rope
geglu
rmsnorm
pretrained-from-scratch
custom_code
Instructions to use vprojectx/Lewis-44M-Bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vprojectx/Lewis-44M-Bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="vprojectx/Lewis-44M-Bert", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("vprojectx/Lewis-44M-Bert", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from vprojectx/Lewis-44M-Bert: direct link, hf CLI and curl.
- Browser
- Download file 2.12 MB
-
https://huggingface.co/vprojectx/Lewis-44M-Bert/resolve/main/tokenizer.json
- Command line
-
hf download hf://vprojectx/Lewis-44M-Bert/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/vprojectx/Lewis-44M-Bert/resolve/main/tokenizer.json
2.12 MB
File too large to display, you can check the raw version instead.