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
-
Add robust LLM relabel pipeline and enforce contiguous title
fed9d99 -
set gpt-5.4-mini default token pricing
8165cc3 -
feat: add concurrency and token/cost telemetry for llm relabel runs
7c5b41e -
feat: add tool-call based llm relabel pipeline and update dataset pointer
e964ae5 -
chore: checkpoint current training and manual relabel progress
efb213a
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Add tests for combo generator
1bef818 -
Add balanced focus dataset generator
651ad49 -
Add path-aware focus dataset support
1e1bc1f
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Train virtual-shard anime parser
359ff82
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Organize parser modules and tools
8c50d16