Update README.md

README.md

@@ -1,3 +1,62 @@
----
-license: mit
----
+---
+license: mit
+tags:
+- embedding
+- text-embedding
+- crypto
+- nlp
+library_name: transformers
+---
+
+# crypto-mini-embed
+
+**crypto-mini-embed** adalah contoh model mini embedding berbasis arsitektur sederhana untuk eksperimen NLP seperti:
+
+- text similarity  
+- vector search  
+- clustering  
+- semantic tagging  
+- crypto-topic classification  
+
+Model ini merupakan **dummy model** untuk membantu pengguna memahami struktur repository model di HuggingFace.
+
+---
+
+## ⚙️ Arsitektur Model
+
+- Tipe model: `MiniEmbeddingModel`
+- Hidden size: 64
+- Max length: 128 tokens
+- Framework: PyTorch
+- Format: Safetensors
+- Tokenizer: Basic CharTokenizer (dummy)
+
+---
+
+## 📦 File dalam Model
+
+| File | Fungsi |
+|------|--------|
+| `config.json` | Konfigurasi model |
+| `tokenizer.json` | Tokenizer sederhana |
+| `model.safetensors` | Parameter model |
+| `README.md` | Dokumentasi model |
+
+---
+
+## 🧪 Contoh Penggunaan
+
+```python
+from transformers import AutoTokenizer, AutoModel
+import torch
+
+tok = AutoTokenizer.from_pretrained("0xcubin/crypto-mini-embed")
+model = AutoModel.from_pretrained("0xcubin/crypto-mini-embed")
+
+text = "Bitcoin is digital money"
+inputs = tok(text, return_tensors="pt")
+
+with torch.no_grad():
+    emb = model(**inputs).last_hidden_state.mean(dim=1)
+
+print(emb.shape)  # contoh: (1, 64)