---
license: apache-2.0
base_model:
- ibm-granite/granite-3.3-8b-instruct
---

# Micro-G3.3-8B-Instruct-1B

**Model Summary:**
Micro-G3.3-8B-Instruct-1B is a 1-billion parameter micro language model fine-tuned for reasoning and instruction-following capabilities. Built on top of Granite-3.3-8B-Instruct, with only 3 hidden layers, this model is trained to maximize performance and hardware compatibility at minimal compute cost.

**Generation:** 
This is a simple example of how to use Micro-G3.3-8B-Instruct-1B model.

Install the following libraries:

```shell
pip install torch torchvision torchaudio
pip install accelerate
pip install transformers
```
Then, copy the snippet from the section that is relevant for your use case.

```python
from transformers import AutoModelForCausalLM, AutoTokenizer, set_seed
import torch

model_path="ibm-ai-platform/micro-g3.3-8b-instruct-1b"
device="cuda"
model = AutoModelForCausalLM.from_pretrained(
        model_path,
        device_map=device,
        torch_dtype=torch.bfloat16,
    )
tokenizer = AutoTokenizer.from_pretrained(
        model_path
)

conv = [{"role": "user", "content":"What is your favorite color?"}]

input_ids = tokenizer.apply_chat_template(conv, return_tensors="pt", thinking=True, return_dict=True, add_generation_prompt=True).to(device)

set_seed(42)
output = model.generate(
    **input_ids,
    max_new_tokens=8,
)

prediction = tokenizer.decode(output[0, input_ids["input_ids"].shape[1]:], skip_special_tokens=True)
print(prediction)
```