Image-Text-to-Text
Transformers
Safetensors
PEFT
qwen3_5_moe
classification
structured-prediction
multimodal
lora
Instructions to use suryatmodulus/GPC-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suryatmodulus/GPC-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="suryatmodulus/GPC-1")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("suryatmodulus/GPC-1") model = AutoModelForMultimodalLM.from_pretrained("suryatmodulus/GPC-1", device_map="auto") - PEFT
How to use suryatmodulus/GPC-1 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use suryatmodulus/GPC-1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "suryatmodulus/GPC-1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "suryatmodulus/GPC-1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/suryatmodulus/GPC-1
- SGLang
How to use suryatmodulus/GPC-1 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 "suryatmodulus/GPC-1" \ --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": "suryatmodulus/GPC-1", "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 "suryatmodulus/GPC-1" \ --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": "suryatmodulus/GPC-1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use suryatmodulus/GPC-1 with Docker Model Runner:
docker model run hf.co/suryatmodulus/GPC-1
| { | |
| "model": "gpc-1", | |
| "messages": [{"role": "user", "content": "A 200 cm rail is filled to 75%. Report filled length."}], | |
| "response_format": {"type": "json_schema", "json_schema": {"name": "rail", "strict": true, "schema": {"type": "object", "properties": {"filled_length": {"type": "number", "minimum": 0, "maximum": 200}}, "required": ["filled_length"], "additionalProperties": false}}}, | |
| "gpc1": {"mode": "numeric101", "numeric_fields": [{"key": "filled_length", "description": "filled rail length", "minimum": 0, "maximum": 200, "unit": "cm"}]}, | |
| "stream": false | |
| } | |