Here is a code to create this tiny model:
```python
import os
from transformers import AutoTokenizer
from transformers import Zamba2Config, Zamba2ForCausalLM
# === Step 1: Define tiny model config ===
config = Zamba2Config(
d_model=16,
n_layer=46, # Match number of Mamba/Hybrid blocks
d_state=32,
expand=2,
conv_kernel=3,
vocab_size=50280,
hidden_size=16
)
# === Step 2: Create model from config ===
model = Zamba2ForCausalLM(config)
# === Step 3: Load or create tokenizer ===
# If tokenizer is not specific to Zamba2, reuse any tokenizer (e.g., from Mamba)
tokenizer = AutoTokenizer.from_pretrained("Zyphra/Zamba2-2.7B")
# === Step 4: Save model and tokenizer ===
output_dir = "./tiny-zamba2"
os.makedirs(output_dir, exist_ok=True)
model.save_pretrained(output_dir, safe_serialization=False)
tokenizer.save_pretrained(output_dir)
```
