enesyila
/

ota-mdeberta-v3-base

@@ -11,7 +11,7 @@ language:
 <!-- Provide a quick summary of what the model is/does. -->
-This is a masked‐language (fill‐mask) model for classical Ottoman Turkish, fine-tuned from the microsoft/mdeberta-v3-base checkpoint. It was trained on a corpus of **38,732,566 tokens** drawn from **141 literary works** in poetry and prose composed between the 15th and 20th centuries.
 ## Model Details
 Unlike FacebookAI/xlm-roberta-base, the tokenizer of microsoft/mdeberta-v3-base recognizes characters in IJMES transliteration alphabet, such as Ḥ and ẓ.
@@ -92,7 +92,7 @@ for r in results:
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-The training data consists of 141 Ottoman Turkish works written between 15 and 20th centuries. The dataset will be released soon.
 #### Preprocessing

 <!-- Provide a quick summary of what the model is/does. -->
+This is a masked‐language (fill‐mask) model for classical Ottoman Turkish, fine-tuned from the microsoft/mdeberta-v3-base checkpoint. It was trained on a corpus of **38,732,566** drawn from **144 literary works** in poetry and prose composed between the 15th and 20th centuries.
 ## Model Details
 Unlike FacebookAI/xlm-roberta-base, the tokenizer of microsoft/mdeberta-v3-base recognizes characters in IJMES transliteration alphabet, such as Ḥ and ẓ.
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+The training data consists of 144 Ottoman Turkish works written between 15 and 20th centuries. The dataset will be released soon.
 #### Preprocessing

notebook.ipynb CHANGED Viewed

@@ -23,7 +23,7 @@
         "| **Language**   | Ottoman Turkish (1500–1928)                  |\n",
         "| **License**    | CC-BY-NC-4.0                                 |\n",
         "\n",
-        "> _Fine-tuned on 38 million tokens from 141 Ottoman literary works._\n"
       ]
     },
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             "Requirement already satisfied: transformers in /usr/local/lib/python3.11/dist-packages (4.52.4)\n",
             "Requirement already satisfied: torch in /usr/local/lib/python3.11/dist-packages (2.6.0+cu124)\n",
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             "/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
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             "Device set to use cpu\n"
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@@ -416,16 +416,16 @@
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           "text": [
             "1. Ne yanar kimse bana âteş-i dil özge\n",
             "   Score: 0.5893\n",
@@ -469,16 +469,16 @@
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             "Ol perîde melek kim beñzemez insân aña 0.08625990897417068\n",
             "Ol perî gibi melek kim beñzemez insân aña 0.07037308067083359\n",
@@ -507,16 +507,16 @@
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             "Input: hâl kâfir, zülf kâfir, [MASK] kâfir el amân\n",
             "  - hâl kâfir, zülf kâfir, dil kâfir el amân (0.087)\n",
@@ -549,18 +549,88 @@
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       "source": [
         "### 5.3 Finding the Best Option\n",
         "\n",
         "The code below takes a sentence with an unknown word or words first. Then, according to the candidate words the user gives, it calculates the probability of each candidate in the context.\n",
         "At the end of the code block, you can give your own examples with candidates and the model will return the result. Note that the model is still under development, so it might give wrong results."
-      ],
-      "metadata": {
-        "id": "ZwsjAo0Omnid"
-      }
     },
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       "source": [
         "from transformers import AutoTokenizer, AutoModelForMaskedLM\n",
         "import torch\n",
@@ -641,76 +711,6 @@
         "    (\"Nes̱r: Ḥaḳḳâ ve {} âsmân-ı bî-hemtâ bir saḳf-ı muʿallâdur\", [\"s̱ümme ḥaḳḳâ\", \"peyġambere\", \"güle\"])\n",
         "]\n",
         "evaluate_templates(examples)\n"
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-            "\n",
-            "Example #1\n",
-            "Template : Gel ey ḥarîf şimdi {} ḳabûl ḳıl\n",
-            "Candidates: ['nasîḥat', 'vardı']\n",
-            "Scores    :\n",
-            "  nasîḥat: 102.6882\n",
-            "  vardı: 21.8411\n",
-            "→ Best candidate: 'nasîḥat'\n",
-            "\n",
-            "Example #2\n",
-            "Template : ʿAḳlı {} gitdi\n",
-            "Candidates: ['başından', 'baş', 'başına']\n",
-            "Scores    :\n",
-            "  başından: 46.6133\n",
-            "  baş: 20.9694\n",
-            "  başına: 47.1951\n",
-            "→ Best candidate: 'başına'\n",
-            "\n",
-            "Example #3\n",
-            "Template : Gerçi der-nâfe-i {} âhû-yı Ḫuten mî-pervered\n",
-            "Candidates: ['ḫod', 'çiy', 'muġân']\n",
-            "Scores    :\n",
-            "  ḫod: 69.5998\n",
-            "  çiy: 52.6196\n",
-            "  muġân: 84.7577\n",
-            "→ Best candidate: 'muġân'\n",
-            "\n",
-            "Example #4\n",
-            "Template : Ceydâ sözin işidicek, taḥammül idemedi, güldi ve yüzin açdı ve {}\n",
-            "Candidates: ['eyitdi', 'gitti', 'Feraḥ']\n",
-            "Scores    :\n",
-            "  eyitdi: 76.0302\n",
-            "  gitti: 29.0941\n",
-            "  Feraḥ: 73.1478\n",
-            "→ Best candidate: 'eyitdi'\n",
-            "\n",
-            "Example #5\n",
-            "Template : Eyledi {} ʿaṭâsı âb-ı luṭfı terbiyet\n",
-            "Candidates: ['mihr-i', 'gül', 'ḳıldı']\n",
-            "Scores    :\n",
-            "  mihr-i: 106.7442\n",
-            "  gül: 26.9753\n",
-            "  ḳıldı: 67.1779\n",
-            "→ Best candidate: 'mihr-i'\n",
-            "\n",
-            "Example #6\n",
-            "Template : Nes̱r: Ḥaḳḳâ ve {} âsmân-ı bî-hemtâ bir saḳf-ı muʿallâdur\n",
-            "Candidates: ['s̱ümme ḥaḳḳâ', 'peyġambere', 'güle']\n",
-            "Scores    :\n",
-            "  s̱ümme ḥaḳḳâ: 243.4302\n",
-            "  peyġambere: 95.3403\n",
-            "  güle: 53.3356\n",
-            "→ Best candidate: 's̱ümme ḥaḳḳâ'\n"
-          ]
-        }
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         "| **Language**   | Ottoman Turkish (1500–1928)                  |\n",
         "| **License**    | CC-BY-NC-4.0                                 |\n",
         "\n",
+        "> _Fine-tuned on 38 million tokens from 144 Ottoman literary works._\n"
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             "Requirement already satisfied: transformers in /usr/local/lib/python3.11/dist-packages (4.52.4)\n",
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             "1. Ne yanar kimse bana âteş-i dil özge\n",
             "   Score: 0.5893\n",
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           "text": [
             "Ol perîde melek kim beñzemez insân aña 0.08625990897417068\n",
             "Ol perî gibi melek kim beñzemez insân aña 0.07037308067083359\n",
       "cell_type": "code",
       "execution_count": 5,
       "metadata": {
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           "text": [
             "Input: hâl kâfir, zülf kâfir, [MASK] kâfir el amân\n",
             "  - hâl kâfir, zülf kâfir, dil kâfir el amân (0.087)\n",
     },
     {
       "cell_type": "markdown",
+      "metadata": {
+        "id": "ZwsjAo0Omnid"
+      },
       "source": [
         "### 5.3 Finding the Best Option\n",
         "\n",
         "The code below takes a sentence with an unknown word or words first. Then, according to the candidate words the user gives, it calculates the probability of each candidate in the context.\n",
         "At the end of the code block, you can give your own examples with candidates and the model will return the result. Note that the model is still under development, so it might give wrong results."
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "collapsed": true,
+        "id": "fMLeaxJ0mY-g",
+        "outputId": "49002a75-bd80-40af-8b99-11b722795f37"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\n",
+            "Example #1\n",
+            "Template : Gel ey ḥarîf şimdi {} ḳabûl ḳıl\n",
+            "Candidates: ['nasîḥat', 'vardı']\n",
+            "Scores    :\n",
+            "  nasîḥat: 102.6882\n",
+            "  vardı: 21.8411\n",
+            "→ Best candidate: 'nasîḥat'\n",
+            "\n",
+            "Example #2\n",
+            "Template : ʿAḳlı {} gitdi\n",
+            "Candidates: ['başından', 'baş', 'başına']\n",
+            "Scores    :\n",
+            "  başından: 46.6133\n",
+            "  baş: 20.9694\n",
+            "  başına: 47.1951\n",
+            "→ Best candidate: 'başına'\n",
+            "\n",
+            "Example #3\n",
+            "Template : Gerçi der-nâfe-i {} âhû-yı Ḫuten mî-pervered\n",
+            "Candidates: ['ḫod', 'çiy', 'muġân']\n",
+            "Scores    :\n",
+            "  ḫod: 69.5998\n",
+            "  çiy: 52.6196\n",
+            "  muġân: 84.7577\n",
+            "→ Best candidate: 'muġân'\n",
+            "\n",
+            "Example #4\n",
+            "Template : Ceydâ sözin işidicek, taḥammül idemedi, güldi ve yüzin açdı ve {}\n",
+            "Candidates: ['eyitdi', 'gitti', 'Feraḥ']\n",
+            "Scores    :\n",
+            "  eyitdi: 76.0302\n",
+            "  gitti: 29.0941\n",
+            "  Feraḥ: 73.1478\n",
+            "→ Best candidate: 'eyitdi'\n",
+            "\n",
+            "Example #5\n",
+            "Template : Eyledi {} ʿaṭâsı âb-ı luṭfı terbiyet\n",
+            "Candidates: ['mihr-i', 'gül', 'ḳıldı']\n",
+            "Scores    :\n",
+            "  mihr-i: 106.7442\n",
+            "  gül: 26.9753\n",
+            "  ḳıldı: 67.1779\n",
+            "→ Best candidate: 'mihr-i'\n",
+            "\n",
+            "Example #6\n",
+            "Template : Nes̱r: Ḥaḳḳâ ve {} âsmân-ı bî-hemtâ bir saḳf-ı muʿallâdur\n",
+            "Candidates: ['s̱ümme ḥaḳḳâ', 'peyġambere', 'güle']\n",
+            "Scores    :\n",
+            "  s̱ümme ḥaḳḳâ: 243.4302\n",
+            "  peyġambere: 95.3403\n",
+            "  güle: 53.3356\n",
+            "→ Best candidate: 's̱ümme ḥaḳḳâ'\n"
+          ]
+        }
+      ],
       "source": [
         "from transformers import AutoTokenizer, AutoModelForMaskedLM\n",
         "import torch\n",
         "    (\"Nes̱r: Ḥaḳḳâ ve {} âsmân-ı bî-hemtâ bir saḳf-ı muʿallâdur\", [\"s̱ümme ḥaḳḳâ\", \"peyġambere\", \"güle\"])\n",
         "]\n",
         "evaluate_templates(examples)\n"
       ]
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