Create README.md

README.md

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+---
+language:
+- en
+license: mit
+tags:
+- text-generation
+- style-transfer
+- rewriting
+- humanization
+- seq2seq
+- bart
+- evaluation
+- bertscore
+- rouge
+- chrf
+library_name: transformers
+base_model: facebook/bart-base
+pipeline_tag: text-generation
+---
+
+# cive202/humanize-ai-text-bart-base
+
+Fine-tuned **BART-base** (`facebook/bart-base`) for **AI → Human rewriting** (“humanization”) via prefix-based conditional generation.
+
+- **Architecture**: encoder–decoder (seq2seq)  
+- **Parameters**: ~139M  
+- **Task format**: `humanize: {ai_text}` → `{human_text}`  
+
+---
+
+## Quickstart
+
+```bash
+pip install -U "transformers>=4.40.0" torch sentencepiece
+```
+
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+model_id = "cive202/humanize-ai-text-bart-base"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
+
+ai_text = "Large language models often produce fluent, structured prose with recognizable regularities..."
+
+inputs = tokenizer("humanize: " + ai_text, return_tensors="pt", truncation=True)
+
+out = model.generate(
+    **inputs,
+    max_new_tokens=256,
+    num_beams=4,
+)
+
+print(tokenizer.decode(out[0], skip_special_tokens=True))
+```
+
+---
+
+## Training note (important)
+
+This checkpoint corresponds to a **smoke-test / pipeline validation run**, not a full training run.
+
+Saved config characteristics:
+
+- `max_steps = 10`  
+- `max_train_samples = 128`  
+- `num_train_epochs = 1`  
+
+⚠️ Interpret results below as a **lower-bound baseline**, not a fully optimized model.
+
+---
+
+## Dataset
+
+Parallel chunk pairs created via sentence-aware chunking:
+
+- **Train**: 25,140 pairs  
+- **Validation**: 1,390  
+- **Test**: 1,390  
+
+### Preprocessing
+
+- Sentence tokenization (NLTK)  
+- Greedy token packing (≤200 tokens)  
+- Filtering short pairs (<10 words)  
+- Document-disjoint splits  
+
+---
+
+## Evaluation (test n = 1,390)
+
+### Reference similarity
+
+- **BERTScore F1**: **0.9088**  
+- **ROUGE-L**: **0.4448**  
+- **chrF++**: **46.4131**  
+
+### Fluency proxy
+
+- **GPT-2 PPL (output)**: **26.6919**  
+- **GPT-2 PPL (human)**: **23.6912**  
+
+### Style shift
+
+- **Mean marker shift**: **0.6513**  
+
+This baseline partially shifts text toward human-like distributions but is limited by minimal training.
+
+---
+
+## Limitations
+
+- Not a fully trained model (smoke-test configuration)  
+- Limited style transformation strength  
+- No guarantee of bypassing AI detectors  
+- Lower performance compared to larger/full runs  
+
+---
+
+## Research context
+
+Part of the unpublished 2026 manuscript:
+
+**“Rewriting the Machine: Encoder-Decoder vs. Decoder-Only Transformers for AI-to-Human Text Style Transfer”**
+
+- Status: Not published  
+- Link: [ADD WHEN AVAILABLE]  
+
+---
+
+## License
+
+MIT (placeholder). Ensure compatibility with `facebook/bart-base`.