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
File size: 197 Bytes
ee692c2 | 1 2 3 4 5 6 7 8 9 10 | {
"bos_token": "<s>",
"eos_token": "</s>",
"mask_token": "<mask>",
"model_max_length": 512,
"pad_token": "<pad>",
"tokenizer_class": "PreTrainedTokenizerFast",
"unk_token": "<unk>"
}
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