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
colab: 加上onnx/onnxruntime依赖
Browse files- colab_train.py +1 -1
colab_train.py
CHANGED
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@@ -76,7 +76,7 @@ print("\n" + "=" * 60)
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print("STEP 3: Install dependencies")
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print("=" * 60)
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# Colab comes with PyTorch + CUDA pre-installed. Just install the extras.
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run("pip install transformers accelerate seqeval")
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# ── 4. Verify GPU ──────────────────────────────────────────────
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print("\n" + "=" * 60)
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print("STEP 3: Install dependencies")
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print("=" * 60)
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# Colab comes with PyTorch + CUDA pre-installed. Just install the extras.
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+
run("pip install transformers accelerate seqeval onnx onnxruntime")
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# ── 4. Verify GPU ──────────────────────────────────────────────
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print("\n" + "=" * 60)
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