Add BERTopic model

README.md

@@ -0,0 +1,72 @@
+
+---
+tags:
+- bertopic
+library_name: bertopic
+pipeline_tag: text-classification
+---
+
+# rag-topic-model
+
+This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model. 
+BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets. 
+
+## Usage 
+
+To use this model, please install BERTopic:
+
+```
+pip install -U bertopic
+```
+
+You can use the model as follows:
+
+```python
+from bertopic import BERTopic
+topic_model = BERTopic.load("ppuva1/rag-topic-model")
+
+topic_model.get_topic_info()
+```
+
+## Topic overview
+
+* Number of topics: 3
+* Number of training documents: 201
+
+<details>
+  <summary>Click here for an overview of all topics.</summary>
+  
+  | Topic ID | Topic Keywords | Topic Frequency | Label | 
+|----------|----------------|-----------------|-------| 
+| -1 | charge - on - account - seeing - random | 75 | -1_charge_on_account_seeing | 
+| 0 | my - to - klarna - the - it | 7 | 0_my_to_klarna_the | 
+| 1 | refund - my - nike - for - store | 119 | 1_refund_my_nike_for |
+  
+</details>
+
+## Training hyperparameters
+
+* calculate_probabilities: False
+* language: None
+* low_memory: False
+* min_topic_size: 10
+* n_gram_range: (1, 1)
+* nr_topics: None
+* seed_topic_list: None
+* top_n_words: 10
+* verbose: False
+* zeroshot_min_similarity: 0.7
+* zeroshot_topic_list: None
+
+## Framework versions
+
+* Numpy: 2.0.2
+* HDBSCAN: 0.8.40
+* UMAP: 0.5.7
+* Pandas: 2.2.3
+* Scikit-Learn: 1.6.1
+* Sentence-transformers: 3.4.1
+* Transformers: 4.48.2
+* Numba: 0.60.0
+* Plotly: 6.0.0
+* Python: 3.9.21

config.json

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+{
+  "calculate_probabilities": false,
+  "language": null,
+  "low_memory": false,
+  "min_topic_size": 10,
+  "n_gram_range": [
+    1,
+    1
+  ],
+  "nr_topics": null,
+  "seed_topic_list": null,
+  "top_n_words": 10,
+  "verbose": false,
+  "zeroshot_min_similarity": 0.7,
+  "zeroshot_topic_list": null
+}

topic_embeddings.safetensors

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+oid sha256:de587e014d6a0af6f1f676efdb47fa5bd26b8d8fed32b5c72dfe32dba295d284
+size 4696

topics.json

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+{
+  "topic_representations": {
+    "-1": [
+      [
+        "charge",
+        0.1437641778909261
+      ],
+      [
+        "on",
+        0.1178154768085835
+      ],
+      [
+        "account",
+        0.11021919978363973
+      ],
+      [
+        "seeing",
+        0.1022161186535828
+      ],
+      [
+        "random",
+        0.1022161186535828
+      ],
+      [
+        "saw",
+        0.1022161186535828
+      ],
+      [
+        "my",
+        0.0984618790345695
+      ],
+      [
+        "buy",
+        0.08782214790690118
+      ],
+      [
+        "charged",
+        0.08782214790690118
+      ],
+      [
+        "im",
+        0.0826643998377298
+      ]
+    ],
+    "0": [
+      [
+        "my",
+        0.10390739366309902
+      ],
+      [
+        "to",
+        0.09071191064477435
+      ],
+      [
+        "klarna",
+        0.08118481702761375
+      ],
+      [
+        "the",
+        0.06553510864541155
+      ],
+      [
+        "it",
+        0.058823167261863776
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+      [
+        "and",
+        0.05797918596010623
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+      [
+        "for",
+        0.04867142710037787
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+      [
+        "email",
+        0.04547149587226583
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+      [
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+        0.04540059233774568
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+      [
+        "in",
+        0.04494803747556551
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+    "1": [
+      [
+        "refund",
+        0.11480022821235052
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+      [
+        "my",
+        0.08942725570982173
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+      [
+        "nike",
+        0.08905467107379061
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+      [
+        "for",
+        0.08460308243237606
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+      [
+        "store",
+        0.07534184980024404
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+      [
+        "returned",
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+      [
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+      [
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+      [
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+  "topic_sizes": {
+    "0": 119,
+    "1": 75,
+    "-1": 7
+  },
+  "topic_mapper": [
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+  "topic_labels": {
+    "-1": "-1_charge_on_account_seeing",
+    "0": "0_my_to_klarna_the",
+    "1": "1_refund_my_nike_for"
+  },
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+  "_outliers": 1,
+  "topic_aspects": {}
+}