Fill-Mask
Transformers
Safetensors
English
tolm
babylm
strict-small
masked-language-modeling
factorized
ltg-bert
custom_code
Instructions to use miguelcsx/factorized-natural-dense with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use miguelcsx/factorized-natural-dense with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="miguelcsx/factorized-natural-dense", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("miguelcsx/factorized-natural-dense", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": "<s>", | |
| "eos_token": "</s>", | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "pad_token": "<pad>", | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "unk_token": "<unk>" | |
| } | |