Text Classification
Transformers
Safetensors
English
mimelens
file-type-detection
mime-classification
binary-content
binary-analysis
position-agnostic
libmagic
forensics
packet-inspection
byte-level
custom_code
Eval Results (legacy)
Instructions to use mjbommar/mimelens-001-medium-byte-s2-seq256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mjbommar/mimelens-001-medium-byte-s2-seq256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mjbommar/mimelens-001-medium-byte-s2-seq256", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("mjbommar/mimelens-001-medium-byte-s2-seq256", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Welcome to the community
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