Add config and tokenizer files for HF compatibility

README.md

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+# RoBERTa Multitask Model
+
+This is a multitask model based on RoBERTa, trained for:
+
+- Sentiment Analysis (negative, neutral, positive)
+- Emotion Classification (anger, joy, optimism, sadness)
+- Hate Speech Detection (hate, offensive, neither)
+
+It uses a shared encoder with task-specific heads.
+
+## Usage
+
+```python
+from models.multitask_model import MultiTaskModel
+from transformers import RobertaTokenizer
+
+tokenizer = RobertaTokenizer.from_pretrained("roberta-base")
+model = MultiTaskModel.from_pretrained("SeragAmin/RoBERTa_Multitask")

config.json

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+{
+    "architectures": ["MultiTaskModel"],
+    "model_type": "roberta",
+    "base_model": "roberta-base",
+    "use_lora": true,
+    "lora_config": {
+      "r": 16,
+      "lora_alpha": 32,
+      "target_modules": ["query", "value"],
+      "lora_dropout": 0.05,
+      "bias": "none",
+      "task_type": "SEQ_CLS"
+    },
+    "hidden_size": 768,
+    "intermediate_size": 128,
+    "dropout_prob": 0.1,
+    "task_name_to_id": {
+      "sentiment": 0,
+      "hate": 1,
+      "emotion": 2
+    },
+    "task_num_labels": {
+      "sentiment": 3,
+      "hate": 3,
+      "emotion": 4
+    }
+  }
+  

model.safetensors

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+size 502161328

optimizer.pt

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+size 7142539

rng_state.pth

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+size 14645

scaler.pt

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+size 1383

scheduler.pt

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+oid sha256:d61ba0149b751d1e39c026ac73851376897cba55c305506a2182a5c57fa3c002
+size 1401

training_args.bin

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+oid sha256:3a845e43e718d3bc9f589a4a0f4dcdbf0a25283e0c6196f0754e1890d839007e
+size 5777