Upload 9 files

app.py

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+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+# Define label dictionary (adjust based on your data and model)
+label_dict = {
+    0: "Yanlış Anlama Değil",
+    1: "Yanlış Anlama",
+    # ... other labels (add more if needed)
+}
+
+# Load model and tokenizer
+model_name = "your_model_directory"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+# Select device (GPU if available)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+# User input
+text = st.text_input("Yanlış anlama olup olmadığını kontrol etmek istediğiniz metni girin:")
+
+# Prediction (if text is provided)
+if text:
+    inputs = tokenizer(text, return_tensors='pt').to(device)
+    outputs = model(**inputs)
+    logits = outputs.logits
+    predicted_class_id = torch.argmax(logits, dim=1).item()
+
+    # Handle predicted class ID
+    if predicted_class_id in label_dict:
+        st.write("Tahmin edilen sonuç:", label_dict[predicted_class_id])
+    else:
+        st.write("Tahmin edilen sonuç:", "Model tarafından bilinmeyen bir yanlış anlama türü")

requirements.txt

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+streamlit
+tensorflow
+opencv-python
+scikit-learn
+torch
+torchvision
+matplotlib
+transformers
+sentencepiece
+plotly

your_model_directory/model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2d4f7ddd579efbb0cf5f8164aa985eadc0db314372e12c705ab50af3a35fb7dc
+size 445910108

your_model_directory/special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

your_model_directory/tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}