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
| { | |
| "model_dir": ".", | |
| "onnx": "exports/anime_filename_parser.onnx", | |
| "case_file": "data/parser_regression_cases.json", | |
| "case_count": 26, | |
| "repeat": 20, | |
| "warmup": 20, | |
| "torch_threads": 1, | |
| "ort_threads": 1, | |
| "constrain_bio": true, | |
| "results": [ | |
| { | |
| "name": "pytorch", | |
| "load_ms": 46.3533999864012, | |
| "runs": 520, | |
| "avg_ms": 15.362302694120444, | |
| "p50_ms": 14.245550031773746, | |
| "p95_ms": 22.27204497321509, | |
| "p99_ms": 29.752646028064174, | |
| "min_ms": 10.793900000862777, | |
| "max_ms": 42.94239997398108, | |
| "throughput_fps": 65.09440803967013 | |
| }, | |
| { | |
| "name": "onnxruntime", | |
| "load_ms": 50.916100037284195, | |
| "runs": 520, | |
| "avg_ms": 12.039251922844695, | |
| "p50_ms": 11.899999983143061, | |
| "p95_ms": 13.811619929037988, | |
| "p99_ms": 15.376427990850043, | |
| "min_ms": 9.72980004735291, | |
| "max_ms": 19.285599933937192, | |
| "throughput_fps": 83.06163924541542 | |
| } | |
| ] | |
| } |