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
Diversify synthetic path episode leaves
Browse files
tools/schema_v2_synthetic_augment/src/main.rs
CHANGED
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@@ -963,15 +963,21 @@ fn path_seed_compatible_with_base(kind: PathSeedKind, base_kind: BaseMediaKind)
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}
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fn simple_path_leaf_records() -> Vec<Record> {
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let mut records =
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-
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"schema_v2_synthetic_path_leaf",
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-
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"path_leaf_episode",
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"path_aug",
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)
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char_record_from_spans(
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"file.mkv",
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&[],
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@@ -988,7 +994,7 @@ fn simple_path_leaf_records() -> Vec<Record> {
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"path_leaf_sxe",
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"path_aug",
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),
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];
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const MOVIE_TAGS: [&str; 6] = [
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"Movie",
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}
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fn simple_path_leaf_records() -> Vec<Record> {
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let mut records = Vec::new();
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for episode in 1..=120 {
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let episode_text = format!("{episode:02}");
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let filename = format!("{episode_text}.mkv");
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let template_id = format!("path_leaf_episode_{episode_text}");
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records.push(char_record_from_spans(
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&filename,
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&[(0, episode_text.len(), Entity::Episode)],
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"schema_v2_synthetic_path_leaf",
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&template_id,
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"path_leaf_episode",
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"path_aug",
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));
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}
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records.extend([
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char_record_from_spans(
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"file.mkv",
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&[],
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"path_leaf_sxe",
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"path_aug",
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),
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]);
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const MOVIE_TAGS: [&str; 6] = [
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"Movie",
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