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---
datasets:
- NeelNanda/pile-10k
base_model:
- google/gemma-3-12b-it
---
## Model Details
This model is an int4 model with group_size 128 and symmetric quantization of [google/gemma-3-12b-it](https://huggingface.co/google/gemma-3-12b-it) generated by [intel/auto-round](https://github.com/intel/auto-round) algorithm.
Please follow the license of the original model.
### Inference on CPU/XPU/CUDA
Requirements
```bash
pip install 'auto-round>0.5.1'
pip install 'transformers>=4.52'
```
~~~python
from transformers import AutoProcessor, Gemma3ForConditionalGeneration
from PIL import Image
import requests
import torch
model_id = "OPEA/gemma-3-12b-it-int4-AutoRound"
model = Gemma3ForConditionalGeneration.from_pretrained(
model_id, torch_dtype=torch.bfloat16, device_map="auto").eval()
processor = AutoProcessor.from_pretrained(model_id)
messages = [
{
"role": "system",
"content": [{"type": "text", "text": "You are a helpful assistant."}]
},
{
"role": "user",
"content": [
{"type": "image",
"image": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/bee.jpg"},
{"type": "text", "text": "Describe this image in detail."}
]
}
]
inputs = processor.apply_chat_template(
messages, add_generation_prompt=True, tokenize=True,
return_dict=True, return_tensors="pt"
).to(model.device, dtype=torch.bfloat16)
model.to(torch.bfloat16)
input_len = inputs["input_ids"].shape[-1]
with torch.inference_mode():
generation = model.generate(**inputs, max_new_tokens=100, do_sample=False)
generation = generation[0][input_len:]
decoded = processor.decode(generation, skip_special_tokens=True)
print(decoded)
"""Here's a detailed description of the image:
**Overall Impression:**
The image is a close-up shot of a vibrant garden scene, focusing on a pink cosmos flower with a bumblebee visiting it. The overall feel is natural, colorful, and slightly wild.
**Main Elements:**
* **Cosmos Flower:** The primary focus is a large, pink cosmos flower. It has broad, slightly ruffled petals in a soft pink hue. The center of the flower is a bright"""
~~~
## Generate the model
Here is the sample command to reproduce the model.
```bash
auto-round-mllm \
--model google/gemma-3-12b-it \
--device 0 \
--bits 4 \
--format 'auto_round' \
--output_dir "./tmp_autoround"
``` |