---
language:
- tr
pipeline_tag: text-generation
tags:
- llama
- smollm
- turkish
- text-generation-inference
---

# smollm-turkish-base

Turkish base model with early stopped training

## Model Description

- **Model Type:** LLaMA Architecture
- **Training Framework:** Nanotron
- **Base Tokenizer:** bonur/gpt2-turkish-tokenizer
- **Context Length:** 4096
- **Vocab Size:** 52000
- **Hidden Size:** 576
- **Number of Layers:** 30
- **Number of Attention Heads:** 9
- **Number of Key/Value Heads:** 3

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("bonur/smollm-turkish-base")
tokenizer = AutoTokenizer.from_pretrained("bonur/smollm-turkish-base")

text = "Your prompt here"
inputs = tokenizer(text, return_tensors="pt", padding=True)
outputs = model.generate(
    inputs.input_ids,
    attention_mask=inputs.attention_mask,
    max_new_tokens=100,
    do_sample=True,
    temperature=0.7,
    top_p=0.9
)
result = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(result)
```