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
| { | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "model_max_length": 512, | |
| "bos_token": "<|start|>", | |
| "eos_token": "<|end|>", | |
| "pad_token": "<|pad|>", | |
| "unk_token": "<|unk|>", | |
| "cls_token": "<|cls|>", | |
| "sep_token": "<|sep|>", | |
| "mask_token": "<|mask|>" | |
| } | |