Instructions to use Trendyol/Trendyol-Vision-Master with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Trendyol/Trendyol-Vision-Master with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="Trendyol/Trendyol-Vision-Master")
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)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("Trendyol/Trendyol-Vision-Master")
model = AutoModelForMultimodalLM.from_pretrained("Trendyol/Trendyol-Vision-Master", device_map="auto")
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?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Trendyol/Trendyol-Vision-Master with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Trendyol/Trendyol-Vision-Master"
# 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-Master",
		"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-Master

SGLang

How to use Trendyol/Trendyol-Vision-Master 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-Master" \
    --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-Master",
		"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-Master" \
        --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-Master",
		"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-Master with Docker Model Runner:
```
docker model run hf.co/Trendyol/Trendyol-Vision-Master
```

AstrumQ1CodeQ Yapay zeka işbirliği

by Gokturk97 - opened 8 days ago

Discussion

Gokturk97

8 days ago

Merhaba, ben Göktürk Bağbaşı, bağımsız bir yapay zekâ geliştiricisiyim. Trendyol LLM çalışmalarınızı ilgiyle takip ediyorum. Q1 CodeQ adlı 25B parametreli, 128K bağlamlı, açık kaynak bir model üzerinde çalışıyorum. Eğitim verisinde 200B token Türkçe var, toplamda 302 dil. En büyük darboğazım compute. Compute desteği veya teknik iş birliği için yazılı olarak iletişime geçebilir miyiz? Repo: https://github.com/gokbagbasi-creator/AlaryQ1CodeQ

Gokturk97 changed discussion title from AlaryQ1CodeQ Yapay zeka işbirliği to AstrumQ1CodeQ Yapay zeka işbirliği 8 days ago

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