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---
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license: mit
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language:
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- en
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base_model:
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- google/gemma-3-12b-it
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pipeline_tag: text-generation
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tags:
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- Vision language model (VLM)
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- Slovenian
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---
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# SVILA - Slovenian Vision Language Assistant - is a Vision Language Model for Slovenian.#
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## The model is based on google/gemma-3-12b-it and was fine-tuned on curated instruction-tuning text-image Slovenian dataset using a custom SFT trainer.
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## Dataset is available here: https://clarin.si/repository/xmlui/handle/11356/2050
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## How to use it: ##
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```python
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from transformers import AutoProcessor, Gemma3ForConditionalGeneration
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import torch
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model_id = "GaMS-Beta/SVILA-1-12B"
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model = Gemma3ForConditionalGeneration.from_pretrained(
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model_id, device_map="auto"
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).eval()
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processor = AutoProcessor.from_pretrained(model_id)
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messages = [
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{
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"role": "system",
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"content": [{"type": "text", "text": ""}]
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},
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{
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"role": "user",
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"content": [
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{"type": "image", "image": "https://www.dangerous-business.com/wp-content/uploads/2024/02/DSC02109.jpg"},
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{"type": "text", "text": "Kaj je na sliki?"}
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]
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}
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]
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print(processor.apply_chat_template(messages, tokenize=False))
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inputs = processor.apply_chat_template(
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messages, add_generation_prompt=True, tokenize=True,
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return_dict=True, return_tensors="pt"
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).to(model.device, dtype=torch.bfloat16)
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input_len = inputs["input_ids"].shape[-1]
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with torch.inference_mode():
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generation = model.generate(**inputs, max_new_tokens=500)
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generation = generation[0][input_len:]
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decoded = processor.decode(generation, skip_special_tokens=True)
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print(decoded)
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```
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