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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ModerRAS/AniFileBERT") model = AutoModelForTokenClassification.from_pretrained("ModerRAS/AniFileBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Simplify title-boundary title span heuristic
b7f5465 -
Parallelize Pi RPC title-boundary reviews
f2c565a -
Add Pi RPC title-boundary reviewer backend
fb3fd2d -
Use direct local HTTP for LM Studio reviewer
74e919a -
Add Rust LM Studio title-boundary reviewer
b689df8 -
Document Rust DMHY template recipe schema
5c84315
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Verify low-frequency DMHY generated output
93f322e -
Add low-frequency DMHY audit gate
494b24c -
Refine DMHY template labeling rules
79b4d87 -
Add Rust DMHY template clustering
736c211 -
Add Rust DMHY template recipe applier
7f87a1d