Instructions to use thehekimoghlu/QCOP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thehekimoghlu/QCOP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="thehekimoghlu/QCOP")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("thehekimoghlu/QCOP", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use thehekimoghlu/QCOP with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "thehekimoghlu/QCOP" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "thehekimoghlu/QCOP", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/thehekimoghlu/QCOP
- SGLang
How to use thehekimoghlu/QCOP 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 "thehekimoghlu/QCOP" \ --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": "thehekimoghlu/QCOP", "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 "thehekimoghlu/QCOP" \ --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": "thehekimoghlu/QCOP", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use thehekimoghlu/QCOP with Docker Model Runner:
docker model run hf.co/thehekimoghlu/QCOP
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| **Total Parameters** | ~40B total, 5B active per token (MoE sparse activation) |
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| **Architecture** | Mixture-of-Experts Vision-Language Model (MoE VLM) |
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| **Context Length** | 396,488 tokens |
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| **Precision** | BF16 |
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| **Input** | Image (PNG, JPEG) + Text |
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| **Total Parameters** | ~40B total, 5B active per token (MoE sparse activation) |
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| **Architecture** | Mixture-of-Experts Vision-Language Model (MoE VLM) |
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| **Experts** | 384 experts, 16 active per token |
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| **Context Length** | 396,488 tokens |
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| **Precision** | BF16 |
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| **Input** | Image (PNG, JPEG) + Text |
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