Image-Text-to-Text
Transformers
Safetensors
Turkish
English
internvl_chat
feature-extraction
computer-vision
multimodal
e-commerce
catalog-moderation
vision-language-model
product-understanding
conversational
custom_code
Instructions to use Trendyol/Trendyol-Vision-Flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Trendyol/Trendyol-Vision-Flash with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Trendyol/Trendyol-Vision-Flash", trust_remote_code=True) messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Trendyol/Trendyol-Vision-Flash", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Trendyol/Trendyol-Vision-Flash with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Trendyol/Trendyol-Vision-Flash" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Trendyol/Trendyol-Vision-Flash", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/Trendyol/Trendyol-Vision-Flash
- SGLang
How to use Trendyol/Trendyol-Vision-Flash with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Trendyol/Trendyol-Vision-Flash" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Trendyol/Trendyol-Vision-Flash", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Trendyol/Trendyol-Vision-Flash" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Trendyol/Trendyol-Vision-Flash", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use Trendyol/Trendyol-Vision-Flash with Docker Model Runner:
docker model run hf.co/Trendyol/Trendyol-Vision-Flash
File size: 615 Bytes
3520a83 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "catalog-vlm-inference"
version = "0.1.0"
description = "Minimal inference environment for CQM VLM (vLLM + Qwen3.5)"
requires-python = ">=3.11,<3.12"
dependencies = [
"vllm==0.19.1",
"transformers>=5.0.0",
"qwen_vl_utils>=0.0.14",
"decord>=0.6.0",
"pyyaml>=6.0",
"jsonlines>=4.0.0",
"requests>=2.32.5",
"tqdm>=4.67.1",
"torchvision",
"nvidia-nccl-cu12==2.28.3",
]
[tool.hatch.build.targets.wheel]
packages = ["src"]
[[tool.uv.index]]
url = "https://pypi.org/simple"
default = true
|