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
| { | |
| "total_files": 30, | |
| "batches": 2, | |
| "batch_size": 15, | |
| "min_id": 1, | |
| "prompt_file_prefix": "prompt_", | |
| "output_file": "D:\\WorkSpace\\Android\\MiruPlay\\tools\\anime_parser\\data\\dmhy\\dmhy_weak_llm.jsonl", | |
| "instructions": "For each prompt_NNNNN.txt file, call task(category='deep', load_skills=[], prompt=contents_of_file) and save the JSON result to batch_NNNNN.jsonl" | |
| } |