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")# pip install -U transformers accelerate # 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
Download Dockerfile from suryatmodulus/GPC-1: direct link, hf CLI and curl.
- Browser
- Download file 915 Bytes
-
https://huggingface.co/suryatmodulus/GPC-1/resolve/main/Dockerfile
- Command line
-
hf download hf://suryatmodulus/GPC-1/Dockerfile
-
curl -L -o Dockerfile https://huggingface.co/suryatmodulus/GPC-1/resolve/main/Dockerfile
915 Bytes
| FROM nvidia/cuda:13.0.1-cudnn-runtime-ubuntu24.04 | |
| ENV PYTHONDONTWRITEBYTECODE=1 \ | |
| PYTHONUNBUFFERED=1 \ | |
| HF_HUB_OFFLINE=1 \ | |
| TRANSFORMERS_OFFLINE=1 \ | |
| GPC1_MAX_CONCURRENCY=1 | |
| WORKDIR /srv/gpc1 | |
| RUN apt-get update && apt-get install -y --no-install-recommends python3.12 python3-pip \ | |
| && rm -rf /var/lib/apt/lists/* | |
| COPY requirements.txt ./ | |
| RUN python3.12 -m pip install --no-cache-dir --break-system-packages \ | |
| --index-url https://download.pytorch.org/whl/cu130 torch==2.9.1 torchvision==0.24.1 \ | |
| && python3.12 -m pip install --no-cache-dir --break-system-packages -r requirements.txt | |
| COPY gpc1_server ./gpc1_server | |
| COPY assets ./assets | |
| COPY adapter ./adapter | |
| RUN useradd --create-home --uid 10001 gpc1 && chown -R gpc1:gpc1 /srv/gpc1 | |
| USER gpc1 | |
| EXPOSE 8000 | |
| CMD ["python3.12", "-m", "uvicorn", "gpc1_server.api:app", "--host", "0.0.0.0", "--port", "8000", "--workers", "1", "--no-access-log"] | |