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README.md
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@@ -18,7 +18,6 @@ from transformers import AutoTokenizer, AutoModelForSequenceClassification
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id2label = {0: "negative", 1: "neutral", 2: "positive"}
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tokenizer = AutoTokenizer.from_pretrained("Voicelab/herbert-base-cased-sentiment")
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-
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model = AutoModelForSequenceClassification.from_pretrained("Voicelab/herbert-base-cased-sentiment")
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input = ["Ale fajnie, spadł dzisiaj śnieg! Ulepimy dziś bałwana?"]
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```
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### Overview
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- **Language model:** [allegro/herbert-base-cased](https://huggingface.co/allegro/herbert-base-cased)
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id2label = {0: "negative", 1: "neutral", 2: "positive"}
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tokenizer = AutoTokenizer.from_pretrained("Voicelab/herbert-base-cased-sentiment")
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model = AutoModelForSequenceClassification.from_pretrained("Voicelab/herbert-base-cased-sentiment")
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input = ["Ale fajnie, spadł dzisiaj śnieg! Ulepimy dziś bałwana?"]
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```
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Predicted output:
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```python
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['Ale fajnie, spadł dzisiaj śnieg! Ulepimy dziś bałwana?'] ---> positive
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```
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### Overview
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- **Language model:** [allegro/herbert-base-cased](https://huggingface.co/allegro/herbert-base-cased)
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