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: 600 Bytes
e63569d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"experiment_name": "dmhy-char-full-relabel",
"data_file": "datasets/AnimeName/dmhy_weak_char.jsonl",
"tokenizer_variant": "char",
"vocab_file": "datasets/AnimeName/vocab.char.json",
"vocab_size": 6199,
"max_seq_length": 128,
"hidden_size": 256,
"num_hidden_layers": 4,
"num_attention_heads": 8,
"intermediate_size": 1024,
"train_samples": 619361,
"eval_samples": 12641,
"epochs": 2.0,
"batch_size": 256,
"learning_rate": 8e-05,
"warmup_steps": 300,
"seed": 48,
"device": "cuda",
"fp16": true,
"gradient_accumulation_steps": 1,
"dataloader_num_workers": 4
} |