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twitter-roberta-base-emoji

Text Classification Transformers PyTorch TensorFlow JAX roberta Inference Endpoints
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luisespinosa commited on
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Update README.md

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  1. README.md +21 -21
README.md CHANGED
@@ -46,7 +46,7 @@ labels = [row[1] for row in csvreader if len(row) > 1]
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  model = AutoModelForSequenceClassification.from_pretrained(MODEL)
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  model.save_pretrained(MODEL)
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- text = "Good night 😊"
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  text = preprocess(text)
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  encoded_input = tokenizer(text, return_tensors='pt')
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  output = model(**encoded_input)
@@ -75,24 +75,24 @@ for i in range(scores.shape[0]):
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  Output:
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  ```
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- 1) 😘 0.2637
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- 2) ❤️ 0.1952
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- 3) 💕 0.1171
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- 4) ✨ 0.0927
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- 5) 😊 0.0756
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- 6) 💜 0.046
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- 7) 💙 0.0444
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- 8) 😍 0.0272
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- 9) 😉 0.0228
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- 10) 😎 0.0198
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- 11) 😜 0.0166
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- 12) 😂 0.0132
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- 13) 😁 0.0131
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- 14) ☀ 0.0112
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- 15) 🎄 0.009
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- 16) 💯 0.009
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- 17) 🔥 0.008
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- 18) 📷 0.0057
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- 19) 🇺🇸 0.005
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- 20) 📸 0.0048
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  ```
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  model = AutoModelForSequenceClassification.from_pretrained(MODEL)
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  model.save_pretrained(MODEL)
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+ text = "Looking forward to Christmas"
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  text = preprocess(text)
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  encoded_input = tokenizer(text, return_tensors='pt')
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  output = model(**encoded_input)
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  Output:
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  ```
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+ 1) 🎄 0.5457
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+ 2) 😊 0.1417
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+ 3) 😁 0.0649
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+ 4) 😍 0.0395
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+ 5) ❤️ 0.03
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+ 6) 😜 0.028
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+ 7) ✨ 0.0263
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+ 8) 😉 0.0237
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+ 9) 😂 0.0177
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+ 10) 😎 0.0166
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+ 11) 😘 0.0143
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+ 12) 💕 0.014
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+ 13) 💙 0.0076
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+ 14) 💜 0.0068
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+ 15) 🔥 0.0065
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+ 16) 💯 0.004
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+ 17) 🇺🇸 0.0037
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+ 18) 📷 0.0034
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+ 19) ☀ 0.0033
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+ 20) 📸 0.0021
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  ```