Copy contents from Gladys's repo

Arabic-model/Arabic_model.joblib

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Arabic-model/config.json

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+        "task": "text-classification"
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+}

Arabic-vectorizer/Arabic_vectorizer.joblib

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Arabic-vectorizer/config.json

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+}

Bengali-model/Bengali_model.joblib

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Bengali-model/config.json

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+        "task": "text-classification"
+    }
+}

Bengali-vectorizer/Bengali_vectorizer.joblib

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Bengali-vectorizer/config.json

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+}

Cyrillic-model/Cyrillic_model.joblib

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Cyrillic-model/config.json

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Cyrillic-vectorizer/Cyrillic_vectorizer.joblib

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Cyrillic-vectorizer/config.json

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+}

Devanagari-model/Devanagari_model.joblib

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Devanagari-model/config.json

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Devanagari-vectorizer/Devanagari_vectorizer.joblib

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Devanagari-vectorizer/config.json

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+        "task": "text-classification"
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+}

Ethiopic-model/Ethiopic_model.joblib

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Ethiopic-model/config.json

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Ethiopic-vectorizer/Ethiopic_vectorizer.joblib

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Ethiopic-vectorizer/config.json

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Gujarati-model/Gujarati_model.joblib

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Gujarati-model/config.json

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Gujarati-vectorizer/Gujarati_vectorizer.joblib

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Gujarati-vectorizer/config.json

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Gurmukhi-model/Gurmukhi_model.joblib

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Gurmukhi-model/config.json

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Gurmukhi-vectorizer/Gurmukhi_vectorizer.joblib

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Gurmukhi-vectorizer/config.json

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Hebrew-model/Hebrew_model.joblib

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Hebrew-model/config.json

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Hebrew-vectorizer/Hebrew_vectorizer.joblib

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Hebrew-vectorizer/config.json

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Latin-model/Latin_model.joblib

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Latin-model/config.json

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Latin-vectorizer/Latin_vectorizer.joblib

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Malayalam-model/Malayalam_model.joblib

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Malayalam-vectorizer/Malayalam_vectorizer.joblib

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Myanmar-model/Myanmar_model.joblib

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Myanmar-model/config.json

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+{
+    "sklearn": {
+        "environment": [
+            "scikit-learn==1.5.2"
+        ],
+        "example_input": {
+            "data": [
+                "\u1018\u102f\u200b\u101b\u102c\u1038\u200b\u101e\u200b\u1001\u1004\u103a\u200b\u101e\u100a\u103a\u200b\u1005\u200b\u1000\u103c\u200b\u101d\u200b\u1020\u102c\u200b\u1000\u102d\u102f\u200b\u1016\u1014\u103a\u200b\u1006\u1004\u103a\u1038 \u1010\u1031\u102c\u103a\u200b\u1019\u1030\u200b\u101e\u1031\u102c\u200b\u1021\u200b\u1001\u102b"
+            ]
+        },
+        "model": {
+            "file": "Myanmar_model.joblib"
+        },
+        "model_format": "pickle",
+        "task": "text-classification"
+    }
+}

Myanmar-vectorizer/Myanmar_vectorizer.joblib

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+size 60711

Myanmar-vectorizer/config.json

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+{
+    "sklearn": {
+        "environment": [
+            "scikit-learn==1.5.2"
+        ],
+        "example_input": {
+            "data": [
+                "\u1018\u102f\u200b\u101b\u102c\u1038\u200b\u101e\u200b\u1001\u1004\u103a\u200b\u101e\u100a\u103a\u200b\u1005\u200b\u1000\u103c\u200b\u101d\u200b\u1020\u102c\u200b\u1000\u102d\u102f\u200b\u1016\u1014\u103a\u200b\u1006\u1004\u103a\u1038 \u1010\u1031\u102c\u103a\u200b\u1019\u1030\u200b\u101e\u1031\u102c\u200b\u1021\u200b\u1001\u102b"
+            ]
+        },
+        "model": {
+            "file": "Myanmar_vectorizer.joblib"
+        },
+        "model_format": "pickle",
+        "task": "text-classification"
+    }
+}

Oriya-model/Oriya_model.joblib

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Oriya-model/config.json

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+{
+    "sklearn": {
+        "environment": [
+            "scikit-learn==1.5.2"
+        ],
+        "example_input": {
+            "data": [
+                "\u0b06\u0b26\u0b4d\u0b5f\u0b30\u0b47 \u0b2a\u0b30\u0b2e\u0b47\u0b36\u0b4d\u0b71\u0b30 \u0b38\u0b4d\u0b71\u0b30\u0b4d\u0b17\u0b38\u0b2e\u0b42\u0b39 \u0b13 \u0b2a\u0b43\u0b25\u0b3f\u0b2c\u0b40\u0b15\u0b41 \u0b38\u0b43\u0b37\u0b4d\u0b1f\u0b3f \u0b15\u0b32\u0b47"
+            ]
+        },
+        "model": {
+            "file": "Oriya_model.joblib"
+        },
+        "model_format": "pickle",
+        "task": "text-classification"
+    }
+}

Oriya-vectorizer/Oriya_vectorizer.joblib

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Oriya-vectorizer/config.json

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+{
+    "sklearn": {
+        "environment": [
+            "scikit-learn==1.5.2"
+        ],
+        "example_input": {
+            "data": [
+                "\u0b06\u0b26\u0b4d\u0b5f\u0b30\u0b47 \u0b2a\u0b30\u0b2e\u0b47\u0b36\u0b4d\u0b71\u0b30 \u0b38\u0b4d\u0b71\u0b30\u0b4d\u0b17\u0b38\u0b2e\u0b42\u0b39 \u0b13 \u0b2a\u0b43\u0b25\u0b3f\u0b2c\u0b40\u0b15\u0b41 \u0b38\u0b43\u0b37\u0b4d\u0b1f\u0b3f \u0b15\u0b32\u0b47"
+            ]
+        },
+        "model": {
+            "file": "Oriya_vectorizer.joblib"
+        },
+        "model_format": "pickle",
+        "task": "text-classification"
+    }
+}

README.md

@@ -1,3 +1,11 @@
----
-license: mit
----
+# Language Detect
+
+This repository contains models and vectorizers for identifying languages written in various scripts. Each script has a corresponding model (`model.joblib`) and vectorizer (`vectorizer.joblib`).
+
+## How It Works
+- The `vectorizer.joblib` preprocesses text for the model.
+- The `model.joblib` predicts the language based on the preprocessed input.
+
+## Files
+- `model.joblib`: Trained model for a specific script.
+- `vectorizer.joblib`: Preprocessor required for the corresponding model.

Tamil-model/Tamil_model.joblib

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