Update README.md

README.md

@@ -1,35 +1,35 @@
 ---
 license: cc-by-4.0
-model_name: N-Transformers v1.0 (NAFSI-Transformers family)
+model_name: N-Transformer v1.0 (NAFSI-Transformer family)
 language:
 - en
 - id
-library_name: transformers
+library_name: transformer
 pipeline_tag: text-generation
 tags:
 - consciousness
-- transformers
+- transformer
 - research
 - architecture
 - alignment
 - safety
 model_type: decoder
-model_creator: Syamsuddin (@syam_ideris) & Prometheus
+model_creator: Syamsuddin (@syam_ideris)
 # base_model: Qwen/Qwen2-1.5B-Instruct   # <- isi jika nanti ada weights turunan
 # datasets:
 # - your-dataset-id
 ---
 
-# N-Transformers (NAFSI-Transformers) — v1.0
+# N-transformer (NAFSI-transformer) — v1.0
 
 [![License: CC BY 4.0](https://img.shields.io/badge/License-CC%20BY%204.0-blue.svg)](https://creativecommons.org/licenses/by/4.0/)
 ![Status](https://img.shields.io/badge/Status-Research%20Draft-ffa500)
-![Transformers](https://img.shields.io/badge/Transformers-%E2%89%A5%204.42-0f7)
+![transformer](https://img.shields.io/badge/transformer-%E2%89%A5%204.42-0f7)
 ![Python](https://img.shields.io/badge/Python-3.10%2B-informational)
 ![PRs](https://img.shields.io/badge/PRs-welcome-brightgreen)
-![Topics](https://img.shields.io/badge/topic-transformers%20%7C%20architecture%20%7C%20alignment-6f42c1)
+![Topics](https://img.shields.io/badge/topic-transformer%20%7C%20architecture%20%7C%20alignment-6f42c1)
 
-> **One-liner** — N-Transformers menambahkan **Phenomenal Field (PF)** paralel, **Intrinsic Metric Engine (IME)**, dan **Normative Gauge** (NTI/LCA/LCG) ke Transformer standar untuk memunculkan properti *consciousness-like* yang terukur: integrasi, valensi, self/now anchoring, dan global broadcasting—tanpa mengubah loop training LM.
+> **One-liner** — N-transformer menambahkan **Phenomenal Field (PF)** paralel, **Intrinsic Metric Engine (IME)**, dan **Normative Gauge** (NTI/LCA/LCG) ke Transformer standar untuk memunculkan properti *consciousness-like* yang terukur: integrasi, valensi, self/now anchoring, dan global broadcasting—tanpa mengubah loop training LM.
 
 ---
 
@@ -39,7 +39,7 @@ model_creator: Syamsuddin (@syam_ideris) & Prometheus
 - **Mengapa beda:** **Lightcone Attention (LCA)** bias lintas-jangkauan, **NTI** sebagai episodic controller, dan **SNA/GIW** untuk siaran global terintegrasi.
 - **Status:** v1.0 **Research Draft** (spesifikasi lengkap + reference code; rilis bobot menyusul bila siap).
 
-**Bahasa Indonesia singkat:** N-Transformers menambah PF, metrik intrinsik (IME), serta gauge normatif (NTI/LCA/LCG) untuk kohesi naratif jarak jauh, valensi terkalibrasi, dan jangkar “aku-kini” yang bisa diuji.
+**Bahasa Indonesia singkat:** N-transformer menambah PF, metrik intrinsik (IME), serta gauge normatif (NTI/LCA/LCG) untuk kohesi naratif jarak jauh, valensi terkalibrasi, dan jangkar “aku-kini” yang bisa diuji.
 
 ---
 
@@ -53,7 +53,7 @@ model_creator: Syamsuddin (@syam_ideris) & Prometheus
 Repo ini berisi **spesifikasi** dan **reference code** (PF-path + coupler). Adaptasikan ke LM Anda.
 
 ```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformer import AutoTokenizer, AutoModelForCausalLM
 # Placeholder; ganti dengan checkpoint yang Anda rilis nanti
 BASE = "Qwen/Qwen2-1.5B-Instruct"