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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ModerRAS/AniFileBERT") model = AutoModelForTokenClassification.from_pretrained("ModerRAS/AniFileBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download requirements.txt from ModerRAS/AniFileBERT: direct link, hf CLI and curl.
- Browser
- Download file 232 Bytes
-
https://huggingface.co/ModerRAS/AniFileBERT/resolve/main/requirements.txt
- Command line
-
hf download hf://ModerRAS/AniFileBERT/requirements.txt
-
curl -L -o requirements.txt https://huggingface.co/ModerRAS/AniFileBERT/resolve/main/requirements.txt
232 Bytes
| --extra-index-url https://download.pytorch.org/whl/cu126 | |
| accelerate==1.13.0 | |
| datasets==4.8.5 | |
| numpy==2.4.5 | |
| onnx==1.21.0 | |
| onnxruntime==1.26.0 | |
| onnxscript==0.7.0 | |
| seqeval==1.2.2 | |
| tensorboard>=2.14.0 | |
| torch==2.12.0+cu126 | |
| transformers==5.8.1 | |