Text Classification
Transformers
Safetensors
qwen3
feature-extraction
custom
multi-label
czech
lora
text-embeddings-inference
Instructions to use enuma-elis/qwen-8b-vyhruzky-vulgarity-rasismus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use enuma-elis/qwen-8b-vyhruzky-vulgarity-rasismus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="enuma-elis/qwen-8b-vyhruzky-vulgarity-rasismus")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("enuma-elis/qwen-8b-vyhruzky-vulgarity-rasismus") model = AutoModelForMultimodalLM.from_pretrained("enuma-elis/qwen-8b-vyhruzky-vulgarity-rasismus") - Notebooks
- Google Colab
- Kaggle
Update handler.py
Browse files- handler.py +1 -2
handler.py
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@@ -34,9 +34,8 @@ class MultiOutputClassifier(nn.Module):
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return logits
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class
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def __init__(self, path: str = ""):
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# ... rest of your code stays the same
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"""
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Initialize the handler with the fine-tuned model
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return logits
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class EndpointHandler(): # Back to original name
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def __init__(self, path: str = ""):
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"""
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Initialize the handler with the fine-tuned model
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