---
license: apache-2.0
language:
  - en
  - multilingual
library_name: transformers
pipeline_tag: image-text-to-text
---

# TayaVision — Tiny Aya Vision (Instruct)

```python
import torch
from PIL import Image
from transformers import AutoModelForCausalLM, AutoProcessor

repo = "TrishanuDas/tayavision-alignment"

model = AutoModelForCausalLM.from_pretrained(repo, torch_dtype=torch.bfloat16, trust_remote_code=True)
model = model.to("cuda").eval()

processor = AutoProcessor.from_pretrained(repo, trust_remote_code=True)

image = Image.open("your_image.jpg").convert("RGB")

messages = [
    {"role": "user", "content": [
        {"type": "image"},
        {"type": "text", "text": "Describe this image in detail."},
    ]},
]

inputs = processor.apply_chat_template(
    messages, images=image, add_generation_prompt=True, return_tensors="pt",
)
inputs = {k: v.to("cuda") for k, v in inputs.items()}

with torch.no_grad():
    output_ids = model.generate(**inputs, max_new_tokens=256)

response = processor.tokenizer.decode(
    output_ids[0, inputs["input_ids"].shape[1]:], skip_special_tokens=True,
)
print(response)
```