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README.md
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license: apache-2.0
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---
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```python
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import torch
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import torch.nn as nn
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logits = model(inputs['input_ids'])
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pred_idx = torch.argmax(logits, dim=1).item()
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pred_label = label_map[pred_idx]
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print(f"
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print(f"
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```
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```python
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```
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---
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license: apache-2.0
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datasets:
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- MarkProMaster229/toxic_dialogue
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- MarkProMaster229/synthetic_classification
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language:
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- ru
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pipeline_tag: text-classification
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tags:
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- toxic
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- custom
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- transformer
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- text-classification
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---
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## Model Details
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- Architecture: Custom Transformer
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- Number of parameters: 33,791,235 (~33.8M)
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- Num layers: 4
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- Num attention heads: 8
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- Hidden size: 256
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## Using
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```python
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import torch
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import torch.nn as nn
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logits = model(inputs['input_ids'])
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pred_idx = torch.argmax(logits, dim=1).item()
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pred_label = label_map[pred_idx]
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print(f"text: {text}")
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print(f"class: {pred_label} ({pred_idx})")
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```
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```python
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text: Я люблю тебя
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class: positive (0)
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text: Мне совсем не понравился этот фильм
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class: negative (1)
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text: Кличка моей кошки - Ирис
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class: neutral (2)
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```
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