Instructions to use Reza2kn/Bina-0.1-Koochik with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Reza2kn/Bina-0.1-Koochik with Transformers:

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

pipe = pipeline("image-text-to-text", model="Reza2kn/Bina-0.1-Koochik")
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 AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("Reza2kn/Bina-0.1-Koochik")
model = AutoModelForMultimodalLM.from_pretrained("Reza2kn/Bina-0.1-Koochik", 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=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Reza2kn/Bina-0.1-Koochik with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Reza2kn/Bina-0.1-Koochik"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Reza2kn/Bina-0.1-Koochik",
		"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/Reza2kn/Bina-0.1-Koochik

SGLang

How to use Reza2kn/Bina-0.1-Koochik 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 "Reza2kn/Bina-0.1-Koochik" \
    --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": "Reza2kn/Bina-0.1-Koochik",
		"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 "Reza2kn/Bina-0.1-Koochik" \
        --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": "Reza2kn/Bina-0.1-Koochik",
		"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 Reza2kn/Bina-0.1-Koochik with Docker Model Runner:
```
docker model run hf.co/Reza2kn/Bina-0.1-Koochik
```

Reza2kn commited on Jul 27

Commit

9b5812b

verified ·

1 Parent(s): d013ac3

Update self-references after Koochik repo rename

Browse files

Files changed (1) hide show

README.md +4 -4

README.md CHANGED Viewed

@@ -42,7 +42,7 @@ python -m pip install -U "surya-ocr>=0.20.0"
 Replace `document.pdf` with an image, a PDF, or a folder containing images/PDFs:
 ```bash
-export SURYA_MODEL_CHECKPOINT=Reza2kn/Bina-0.1
 export SURYA_INFERENCE_BACKEND=vllm
 surya_ocr ./document.pdf --output_dir ./bina-output
@@ -70,7 +70,7 @@ Set the environment variables before importing `surya`:
 ```python
 import os
-os.environ["SURYA_MODEL_CHECKPOINT"] = "Reza2kn/Bina-0.1"
 os.environ["SURYA_INFERENCE_BACKEND"] = "vllm"
 from PIL import Image
@@ -113,7 +113,7 @@ python -m pip install -U "surya-ocr>=0.20.0"
 تصاویر/PDFها را قرار دهید:
 ```bash
-export SURYA_MODEL_CHECKPOINT=Reza2kn/Bina-0.1
 export SURYA_INFERENCE_BACKEND=vllm
 surya_ocr ./document.pdf --output_dir ./bina-output
@@ -141,7 +141,7 @@ surya_ocr ./document.pdf --images --output_dir ./bina-output
 ```python
 import os
-os.environ["SURYA_MODEL_CHECKPOINT"] = "Reza2kn/Bina-0.1"
 os.environ["SURYA_INFERENCE_BACKEND"] = "vllm"
 from PIL import Image

 Replace `document.pdf` with an image, a PDF, or a folder containing images/PDFs:
 ```bash
+export SURYA_MODEL_CHECKPOINT=Reza2kn/Bina-0.1-Koochik
 export SURYA_INFERENCE_BACKEND=vllm
 surya_ocr ./document.pdf --output_dir ./bina-output
 ```python
 import os
+os.environ["SURYA_MODEL_CHECKPOINT"] = "Reza2kn/Bina-0.1-Koochik"
 os.environ["SURYA_INFERENCE_BACKEND"] = "vllm"
 from PIL import Image
 تصاویر/PDFها را قرار دهید:
 ```bash
+export SURYA_MODEL_CHECKPOINT=Reza2kn/Bina-0.1-Koochik
 export SURYA_INFERENCE_BACKEND=vllm
 surya_ocr ./document.pdf --output_dir ./bina-output
 ```python
 import os
+os.environ["SURYA_MODEL_CHECKPOINT"] = "Reza2kn/Bina-0.1-Koochik"
 os.environ["SURYA_INFERENCE_BACKEND"] = "vllm"
 from PIL import Image