Fill-Mask
Transformers
Safetensors
English
roformer
binary-analysis
file-type-detection
byte-level
mlm
rope
magic-bytes
security
Eval Results (legacy)
Instructions to use mjbommar/magic-bert-50m-roformer-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mjbommar/magic-bert-50m-roformer-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mjbommar/magic-bert-50m-roformer-mlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mjbommar/magic-bert-50m-roformer-mlm") model = AutoModelForMaskedLM.from_pretrained("mjbommar/magic-bert-50m-roformer-mlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b86126a4b86dc740cbaa9fa30e92b52424362d6fc018d513ee129b33bb32b9a
- Size of remote file:
- 169 MB
- SHA256:
- 6a3261fa9e328c33dacb5c5b25639d6d5014392f1bd13307c866bce39b0abf6c
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