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 model.safetensors from ModerRAS/AniFileBERT: direct link, hf CLI and curl.
- Browser
- Download file 19.2 MB
-
https://huggingface.co/ModerRAS/AniFileBERT/resolve/main/model.safetensors
- Command line
-
hf download hf://ModerRAS/AniFileBERT/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ModerRAS/AniFileBERT/resolve/main/model.safetensors
19.2 MB
- Xet hash:
- 69a0d17159a1985d781b87e77fddec771efa78827ac0e3b2b545e561e8fcd130
- Size of remote file:
- 19.2 MB
- SHA256:
- d4dcccaed27767e9dd2e416ee573ca06d1a579220d9928443e7be1b47b638d37
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.