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
File size: 383 Bytes
f4f4e0e | 1 2 3 4 5 6 7 8 9 | {
"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"
} |