Text Classification
Transformers
ONNX
Safetensors
English
mimelens
file-type-detection
mime-classification
binary-content
binary-analysis
position-agnostic
libmagic
forensics
packet-inspection
bpe
byte-pair-encoding
custom_code
Eval Results (legacy)
Instructions to use mjbommar/mimelens-001-medium-bpe-16k-s1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mjbommar/mimelens-001-medium-bpe-16k-s1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mjbommar/mimelens-001-medium-bpe-16k-s1", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("mjbommar/mimelens-001-medium-bpe-16k-s1", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "model_max_length": 1024, | |
| "padding_side": "right", | |
| "truncation_side": "right", | |
| "pad_token": "[PAD]", | |
| "unk_token": "[UNK]", | |
| "cls_token": "[CLS]", | |
| "sep_token": "[SEP]", | |
| "mask_token": "[MASK]", | |
| "clean_up_tokenization_spaces": false, | |
| "added_tokens_decoder": { | |
| "2": { | |
| "content": "[PAD]", | |
| "lstrip": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "normalized": false, | |
| "special": true | |
| }, | |
| "3": { | |
| "content": "[UNK]", | |
| "lstrip": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "normalized": false, | |
| "special": true | |
| }, | |
| "4": { | |
| "content": "[CLS]", | |
| "lstrip": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "normalized": false, | |
| "special": true | |
| }, | |
| "5": { | |
| "content": "[SEP]", | |
| "lstrip": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "normalized": false, | |
| "special": true | |
| }, | |
| "6": { | |
| "content": "[MASK]", | |
| "lstrip": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "normalized": false, | |
| "special": true | |
| } | |
| } | |
| } |