Image-Text-to-Text
Transformers
TensorBoard
Safetensors
vision-encoder-decoder
Generated from Trainer
Instructions to use invmodel/qa-invgrid-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use invmodel/qa-invgrid-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="invmodel/qa-invgrid-3")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("invmodel/qa-invgrid-3") model = AutoModelForImageTextToText.from_pretrained("invmodel/qa-invgrid-3") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use invmodel/qa-invgrid-3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "invmodel/qa-invgrid-3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "invmodel/qa-invgrid-3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/invmodel/qa-invgrid-3
- SGLang
How to use invmodel/qa-invgrid-3 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 "invmodel/qa-invgrid-3" \ --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": "invmodel/qa-invgrid-3", "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 "invmodel/qa-invgrid-3" \ --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": "invmodel/qa-invgrid-3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use invmodel/qa-invgrid-3 with Docker Model Runner:
docker model run hf.co/invmodel/qa-invgrid-3
- Xet hash:
- 0f47a044e53c36acd9d8fe1ae1b3151c7ace51fd9b07251de7c32ca1213436eb
- Size of remote file:
- 4.79 kB
- SHA256:
- fe25e87658545ab0767d1bf1753f6980fcac5f85594c6b80caf93a0429c98bdf
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