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README.md

@@ -1,32 +1,24 @@
 ---
 language:
 - fa
+license: apache-2.0
 tags:
 - sentiment-analysis
 - text-classification
 - tensorflow
-- transformers
-license: apache-2.0
+- keras
+base_model: HooshvareLab/bert-base-parsbert-uncased
 ---
 
 # ParsBERT Sentiment (Fine-tuned)
 
-This repository contains a Persian sentiment analysis model fine-tuned from `HooshvareLab/bert-base-parsbert-uncased`.
-
-## Sentiment labels (label mapping)
+This repository contains a Persian sentiment model trained using a custom TensorFlow/Keras head on top of ParsBERT.
 
+## Label mapping
 - 0 → Negative
 - 1 → Positive
 - 2 → Neutral
 
-
-## Files
-- Transformer base model (TensorFlow) saved with `save_pretrained`
-- Tokenizer saved with `save_pretrained`
-- Classification head / full-model weights: `bert_sentiment_weights.h5` (Keras weights)
-
-## How to use
-Because the final model is a custom Keras graph, load by:
-1) loading tokenizer and base ParsBERT
-2) rebuilding the same Keras architecture
-3) loading the weights file
+## Notes
+This is a custom Keras architecture, so `pipeline()` may not work automatically.
+Use the provided weights file: `parsbert_sentiment.weights.h5` and rebuild the model architecture as in the training code.

parsbert_base_tf/tf_model.h5

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parsbert_sentiment.weights.h5

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 size 49264

tokenizer.json

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 {
   "version": "1.0",
-  "truncation": null,
-  "padding": null,
+  "truncation": {
+    "direction": "Right",
+    "max_length": 128,
+    "strategy": "LongestFirst",
+    "stride": 0
+  },
+  "padding": {
+    "strategy": {
+      "Fixed": 128
+    },
+    "direction": "Right",
+    "pad_to_multiple_of": null,
+    "pad_id": 0,
+    "pad_type_id": 0,
+    "pad_token": "[PAD]"
+  },
   "added_tokens": [
     {
       "id": 0,