Token Classification
Transformers
ONNX
Safetensors
English
Japanese
Chinese
bert
anime
filename-parsing
Eval Results (legacy)
Instructions to use ModerRAS/AniFileBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModerRAS/AniFileBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ModerRAS/AniFileBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ModerRAS/AniFileBERT") model = AutoModelForTokenClassification.from_pretrained("ModerRAS/AniFileBERT") - Notebooks
- Google Colab
- Kaggle
File size: 1,070 Bytes
f4f4e0e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | {
"created_at": "2026-05-13T15:26:19.767707+00:00",
"source_db": "D:\\WorkSpace\\Python\\dmhy-parser\\dmhy_anime.db",
"output": "data\\dmhy\\dmhy_weak_new.jsonl",
"min_file_id": 689305,
"last_file_id": 1675184,
"db_max_file_id_at_export_start": 1675184,
"limit": null,
"stats": {
"scanned_rows": 985880,
"video_rows": 556778,
"duplicate_basenames": 95422,
"labeled_samples": 378327,
"skipped_no_episode": 82422,
"skipped_no_title": 0,
"skipped_too_short": 606,
"skipped_too_long": 1
},
"label_counts": {
"B-GROUP": 306878,
"B-TITLE": 390543,
"B-EPISODE": 378327,
"B-RESOLUTION": 156089,
"B-SOURCE": 180428,
"O": 1587219,
"I-TITLE": 1401899,
"B-SPECIAL": 29468,
"B-SEASON": 18792,
"I-GROUP": 517
},
"vocab_size": 3000,
"notes": [
"Rows are a snapshot of files.id <= last_file_id.",
"Future incremental export can use --min-id last_file_id+1.",
"Weak labels target GROUP, TITLE, SEASON, and EPISODE; media tags are boundary labels/noise."
],
"examples": []
} |