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README.md

@@ -5,6 +5,7 @@ library_name: peft
 base_model: Qwen/Qwen2.5-1.5B
 tags:
   - lora
+  - peft
   - cognitive-architecture
   - progressive-learning
   - magnitude-pruning
@@ -15,46 +16,82 @@ datasets:
 pipeline_tag: text-generation
 ---
 
-# Progressive Cognitive Architecture — Progressive-LoRA (Qwen 2.5 1.5B)
+# Architettura Cognitiva Progressiva — Progressive-LoRA con Magnitude Pruning (Italiano)
 
-**4-phase progressive training with magnitude pruning (the predecessor to Dream Pruning).**
+**Primo prototipo** — Qwen2.5-1.5B addestrato con architettura cognitiva progressiva a 4 fasi, usando **magnitude pruning** (azzeramento pesi piccoli). Successivamente sostituito da SVD Dream Pruning.
 
-## What is this?
+## 📊 Risultati
 
-This is the original Progressive-LoRA model using **magnitude pruning** (zeroing small weights) instead of SVD Dream Pruning. It was the first version of the progressive cognitive architecture.
+| Metrica | Progressive-LoRA (questo) | Dream-LoRA | Flat-LoRA |
+|---------|--------------------------|-----------|-----------|
+| Accuratezza Esatta | 37.0% ± 0.5 | 58.6% ± 2.9 | 60.6% |
+| Number Sense | 57.7% ± 0.5 | 60.0% ± 0.8 | 0.0% |
+| Metacognizione | 98.5% | 100.0% | 0.0% |
 
-## 📊 Results
+## 🧠 Architettura
 
-| Metric | Progressive-LoRA (this) | Dream-LoRA | Flat-LoRA |
-|--------|------------------------|-----------|-----------|
-| Exact Accuracy | 37.0% ± 0.5 | 58.6% ± 2.9 | 60.6% |
-| Number Sense | 57.7% ± 0.5 | 60.0% ± 0.8 | 0.0% |
-| Metacognition | 98.5% | 100.0% | 0.0% |
+Training progressivo a 4 fasi su dati aritmetici italiani:
+1. **Fondamenta** — Aritmetica esatta
+2. **Consolidamento** — Magnitude pruning + fine-tuning su approssimazioni
+3. **Delega** — Routing complessità: calcolo interno vs. strumento
+4. **Orchestrazione** — Pipeline completa: intuizione → routing → tool → validazione
 
-Dream Pruning (SVD) significantly improved upon magnitude pruning by preserving more of the learned information during compression.
+## 🔧 Configurazione
 
-## 🚀 Quick Start
+| Parametro | Valore |
+|-----------|--------|
+| Modello Base | Qwen/Qwen2.5-1.5B |
+| LoRA Rank | 16 |
+| LoRA Alpha | 32 |
+| Target LoRA | q_proj, k_proj, v_proj, o_proj |
+| Tipo Pruning | Magnitude (azzeramento pesi piccoli) |
+| Lingua Dati | Italiano |
+
+## 🚀 Uso Rapido
 
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 from peft import PeftModel
 
-base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B", device_map="auto")
+base_model = AutoModelForCausalLM.from_pretrained(
+    "Qwen/Qwen2.5-1.5B", device_map="auto", torch_dtype="auto"
+)
 tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-1.5B")
 
-# Note: adapters are in lora_adapters/ subfolder
-model = PeftModel.from_pretrained(base_model, "dexmac/progressive-cognitive-lora", subfolder="lora_adapters")
+model = PeftModel.from_pretrained(
+    base_model,
+    "dexmac/progressive-cognitive-lora",
+    subfolder="lora_adapters"
+)
 
-inputs = tokenizer("Calcola: 347 + 891 =", return_tensors="pt").to(model.device)
-outputs = model.generate(**inputs, max_new_tokens=20)
+messages = [{"role": "user", "content": "Calcola: 342 * 67"}]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=200, temperature=0.1)
 print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 ```
 
-## 📄 Related
+## 🔗 Modelli Correlati
+
+- [**Dream-LoRA (IT)**](https://huggingface.co/dexmac/progressive-cognitive-dream-lora) — Versione migliorata con SVD Dream Pruning
+- [Flat-LoRA (IT)](https://huggingface.co/dexmac/progressive-cognitive-baseline-lora) — Controllo senza fasi
+- [1.5B Dream (EN)](https://huggingface.co/dexmac/progressive-cognitive-dream-lora-en) — Miglior modello (inglese)
+- [GitHub](https://github.com/dexmac221/progressive-cognitive) — Codice sorgente completo
 
-- **Dream-LoRA (improved)**: [dexmac/progressive-cognitive-dream-lora](https://huggingface.co/dexmac/progressive-cognitive-dream-lora)
-- **GitHub**: [dexmac221/progressive-cognitive](https://github.com/dexmac221/progressive-cognitive)
+## 📝 Citation
+
+```bibtex
+@software{progressive_cognitive_2026,
+  author = {Dex Mac},
+  title = {Progressive Cognitive Architecture for LLMs},
+  year = {2026},
+  url = {https://github.com/dexmac221/progressive-cognitive},
+  version = {1.0.0}
+}
+```
 
-## 📜 License
+
+## 📄 License
 
 Apache 2.0
+