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v1v1d1/nayana-gemma3-4b-stage1
nayana-gemma3-4b-stage1 is a image-text-to-text model from v1v1d1. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
Fine-tuned Vision-Language Model using MS-Swift and LoRA adapters.
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From the Hugging Face model README
Fine-tuned Vision-Language Model using MS-Swift and LoRA adapters.
| Parameter | Value |
|---|---|
| LoRA Rank | 16 |
| LoRA Alpha | 32 |
| Batch Size | 2 |
| Learning Rate | 0.0001 |
| Epochs | 1.0 |
| Gradient Accumulation | 4 |
from vllm import LLM, SamplingParams
llm = LLM(
model="v1v1d1/nayana-gemma3-4b-stage1",
gpu_memory_utilization=0.8,
max_model_len=8192,
)
sampling_params = SamplingParams(
temperature=0.0,
max_tokens=512,
)
# Example with image
messages = [{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": "path/to/image.jpg"}},
{"type": "text", "text": "Describe this image in detail."}
]
}]
outputs = llm.chat(messages, sampling_params=sampling_params)
print(outputs[0].outputs[0].text)
from transformers import AutoModelForVision2Seq, AutoProcessor
from PIL import Image
model = AutoModelForVision2Seq.from_pretrained(
"v1v1d1/nayana-gemma3-4b-stage1",
torch_dtype="auto",
device_map="auto"
)
processor = AutoProcessor.from_pretrained("v1v1d1/nayana-gemma3-4b-stage1")
image = Image.open("path/to/image.jpg")
messages = [
{"role": "user", "content": [
{"type": "image"},
{"type": "text", "text": "Describe this image in detail."}
]}
]
text = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = processor(text=[text], images=[image], return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512)
print(processor.decode(outputs[0], skip_special_tokens=True))
@misc{v1v1d1-nayana-gemma3-4b-stage1},
author = {Nayana Project},
title = {nayana-gemma3-4b-stage1},
year = {2026},
publisher = {HuggingFace},
howpublished = {https://huggingface.co/v1v1d1/nayana-gemma3-4b-stage1}
}
This model was trained using the VIVID Dataset Pipeline.
Generated with 🤖 Claude Code