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crypto-mini-embed
0xcubin/crypto-mini-embed
crypto-mini-embed is a machine learning model from 0xcubin. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
crypto-mini-embed adalah contoh model mini embedding berbasis arsitektur sederhana untuk eksperimen NLP seperti:
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At a glance
- Library
- transformers
- License
- mit
- Model type
- crypto_mini_embed
- Access
- Public
- Created
- Dec 11, 2025
- Updated
- Dec 11, 2025
- SHA
- fb82757d
Model card
From the Hugging Face model README
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
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)
- Library
- transformers
- Type
- crypto_mini_embed
- License
- mit
- Created
- Dec 11, 2025
- Updated
- Dec 11, 2025