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_config.json from vprojectx/Lewis-44M-Bert: direct link, hf CLI and curl.
- Browser
- Download file 256 Bytes
-
https://huggingface.co/vprojectx/Lewis-44M-Bert/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://vprojectx/Lewis-44M-Bert/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/vprojectx/Lewis-44M-Bert/resolve/main/tokenizer_config.json
256 Bytes
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "eos_token": "</s>", | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "<unk>" | |
| } | |