Instructions to use dragonstar/image-text-captcha-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dragonstar/image-text-captcha-v2 with Transformers:

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

pipe = pipeline("image-text-to-text", model="dragonstar/image-text-captcha-v2")

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

tokenizer = AutoTokenizer.from_pretrained("dragonstar/image-text-captcha-v2")
model = AutoModelForMultimodalLM.from_pretrained("dragonstar/image-text-captcha-v2", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use dragonstar/image-text-captcha-v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dragonstar/image-text-captcha-v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dragonstar/image-text-captcha-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/dragonstar/image-text-captcha-v2

SGLang

How to use dragonstar/image-text-captcha-v2 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 "dragonstar/image-text-captcha-v2" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dragonstar/image-text-captcha-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "dragonstar/image-text-captcha-v2" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dragonstar/image-text-captcha-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use dragonstar/image-text-captcha-v2 with Docker Model Runner:
```
docker model run hf.co/dragonstar/image-text-captcha-v2
```

image-text-captcha-v2

Commit History

Nov 6, 2024

13:46
Adding `safetensors` variant of this model⁠

SFconvertbot

Verified signature
a61eac4

Sep 11, 2023

22:10
Librarian Bot: Add base_model information to model (#2)⁠

dragonstar +1: librarian-bot

a140595

Jun 2, 2023

23:21
All Done!

dragonstar

b1210e0
23:19
update model card README.md

dragonstar

36f33e1
23:19
Model save

dragonstar

caa3080
23:16
Training in progress, epoch 5

dragonstar

746902d
23:01
Training in progress, epoch 4

dragonstar

475c884
22:46
Training in progress, epoch 3

dragonstar

875427d
22:30
Training in progress, epoch 2

dragonstar

9c3b712
22:15
Training in progress, epoch 1

dragonstar

b33198f
22:02
initial commit

dragonstar

7d28185

Commit History

Nov 6, 2024

Adding `safetensors` variant of this model⁠

Sep 11, 2023

Librarian Bot: Add base_model information to model (#2)⁠

Jun 2, 2023

All Done!

update model card README.md

Model save

Training in progress, epoch 5

Training in progress, epoch 4

Training in progress, epoch 3

Training in progress, epoch 2

Training in progress, epoch 1

initial commit