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README.md

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+# LLM_Detector_Preview_model
+
+**Preview release of an LLM-generated text detector.**
+
+## Model Description
+This model is designed to classify text as Human, Mixed, or AI-generated. It is based on a sequence classification architecture and was trained on a mix of human and AI-generated texts. The model can be used for document, sentence, and token-level analysis.
+
+- **Architecture:** ModernBERT (or compatible Transformer)
+- **Labels:**
+  - 0: Human
+  - 1: Mixed
+  - 2: AI
+
+## Intended Use
+- **For research and curiosity only.**
+- Not for academic, legal, medical, or high-stakes use.
+- Results are easy to bypass and may be unreliable.
+
+## Limitations & Warnings
+- This model is **experimental** and not clinically accurate.
+- It can produce false positives and false negatives.
+- Simple paraphrasing or editing can fool the detector.
+- Do not use for academic integrity, hiring, or legal decisions.
+
+## How It Works
+The model analyzes text and predicts the likelihood of it being human-written, mixed, or AI-generated. It uses statistical patterns learned from training data, but these patterns are not foolproof and can be circumvented.
+
+## Example Usage
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained('Donnyed/LLM_Detector_Preview_model')
+model = AutoModelForSequenceClassification.from_pretrained('Donnyed/LLM_Detector_Preview_model')
+
+text = "Paste your text here."
+inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
+with torch.no_grad():
+    outputs = model(**inputs)
+    probs = torch.softmax(outputs.logits, dim=1)
+    pred = torch.argmax(probs, dim=1).item()
+    print('Prediction:', pred)
+    print('Probabilities:', probs)
+```
+
+## Files Included
+- `model.safetensors` — Model weights
+- `config.json` — Model configuration
+- `tokenizer.json`, `tokenizer_config.json`, `special_tokens_map.json` — Tokenizer files
+
+## License
+Specify your license here (e.g., Apache 2.0, MIT, etc.)
+
+---
+**Maintainer:** [your-username](https://huggingface.co/your-username) 

config.json

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+{
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+    "ModernBertForSequenceClassification"
+  ],
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+  "attention_dropout": 0.0,
+  "bos_token_id": 50281,
+  "classifier_activation": "gelu",
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+  "global_attn_every_n_layers": 3,
+  "global_rope_theta": 160000.0,
+  "gradient_checkpointing": false,
+  "hidden_activation": "gelu",
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "human",
+    "1": "mixed",
+    "2": "ai"
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+  "initializer_cutoff_factor": 2.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 2624,
+  "label2id": {
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+    "human": 0,
+    "mixed": 1
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+  "layer_norm_eps": 1e-05,
+  "local_attention": 128,
+  "local_rope_theta": 10000.0,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "mlp_dropout": 0.0,
+  "model_type": "modernbert",
+  "norm_bias": false,
+  "norm_eps": 1e-05,
+  "num_attention_heads": 16,
+  "num_hidden_layers": 28,
+  "pad_token_id": 50283,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "repad_logits_with_grad": false,
+  "sep_token_id": 50282,
+  "sparse_pred_ignore_index": -100,
+  "sparse_prediction": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.51.3",
+  "vocab_size": 50368
+}

model.safetensors

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optimizer.pt

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rng_state.pth

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scheduler.pt

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special_tokens_map.json

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