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jithinjames
/
iol-ai-2026-solver

Text Generation
Safetensors
qwen2
competition
iol-ai-2026
conversational
4-bit precision
awq
Model card Files Files and versions
xet
Community

Instructions to use jithinjames/iol-ai-2026-solver with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Local Apps Settings
  • vLLM

    How to use jithinjames/iol-ai-2026-solver with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "jithinjames/iol-ai-2026-solver"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "jithinjames/iol-ai-2026-solver",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/jithinjames/iol-ai-2026-solver
  • SGLang

    How to use jithinjames/iol-ai-2026-solver 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 "jithinjames/iol-ai-2026-solver" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "jithinjames/iol-ai-2026-solver",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    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 "jithinjames/iol-ai-2026-solver" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "jithinjames/iol-ai-2026-solver",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use jithinjames/iol-ai-2026-solver with Docker Model Runner:

    docker model run hf.co/jithinjames/iol-ai-2026-solver
iol-ai-2026-solver
9.99 GB
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  • 1 contributor
History: 37 commits
jithinjames's picture
jithinjames
Bump sampling temperature 0.3->0.5 -- single-variable test on v11 (score 0.1303, best-of-day banked)
cb33f4a verified 12 days ago
  • .gitattributes
    1.52 kB
    initial commit 15 days ago
  • LICENSE
    11.3 kB
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  • README.md
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  • config.json
    841 Bytes
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  • generation_config.json
    243 Bytes
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  • merges.txt
    1.67 MB
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  • model-00001-of-00003.safetensors
    3.99 GB
    xet
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  • model-00002-of-00003.safetensors
    3.97 GB
    xet
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  • model-00003-of-00003.safetensors
    2.02 GB
    xet
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  • model.safetensors.index.json
    107 kB
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  • script.py
    10.1 kB
    Bump sampling temperature 0.3->0.5 -- single-variable test on v11 (score 0.1303, best-of-day banked) 12 days ago
  • tokenizer.json
    7.03 MB
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  • tokenizer_config.json
    7.31 kB
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  • vocab.json
    2.78 MB
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