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Neurazum
/
Tbai-DPA-1.0

Text Generation
Transformers
Safetensors
Turkish
text
image
brain
dementia
mri
fmri
health
diagnosis
diseases
alzheimer
parkinson
comment
doctor
vbai
tbai
bai
Model card Files Files and versions
xet
Community

Instructions to use Neurazum/Tbai-DPA-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Neurazum/Tbai-DPA-1.0 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="Neurazum/Tbai-DPA-1.0")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Neurazum/Tbai-DPA-1.0", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use Neurazum/Tbai-DPA-1.0 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Neurazum/Tbai-DPA-1.0"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Neurazum/Tbai-DPA-1.0",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/Neurazum/Tbai-DPA-1.0
  • SGLang

    How to use Neurazum/Tbai-DPA-1.0 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 "Neurazum/Tbai-DPA-1.0" \
        --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": "Neurazum/Tbai-DPA-1.0",
    		"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 "Neurazum/Tbai-DPA-1.0" \
            --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": "Neurazum/Tbai-DPA-1.0",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use Neurazum/Tbai-DPA-1.0 with Docker Model Runner:

    docker model run hf.co/Neurazum/Tbai-DPA-1.0
Tbai-DPA-1.0
2.19 GB
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  • 1 contributor
History: 10 commits
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eyupipler
Update README.md
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