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playdev7
/
theseed

Text Generation
Transformers
Safetensors
Korean
English
conversational
mixtral
Model card Files Files and versions
xet
Community

Instructions to use playdev7/theseed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use playdev7/theseed with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="playdev7/theseed")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("playdev7/theseed", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use playdev7/theseed with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "playdev7/theseed"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "playdev7/theseed",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/playdev7/theseed
  • SGLang

    How to use playdev7/theseed 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 "playdev7/theseed" \
        --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": "playdev7/theseed",
    		"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 "playdev7/theseed" \
            --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": "playdev7/theseed",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use playdev7/theseed with Docker Model Runner:

    docker model run hf.co/playdev7/theseed
theseed
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  • 1 contributor
History: 52 commits
playdev7's picture
playdev7
Update README.md
4c538a5 verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    592 Bytes
    Update README.md about 2 years ago
  • config.json
    600 Bytes
    Update config.json about 2 years ago
  • git_ignore
    43 Bytes
    theseed-v0.2 about 2 years ago
  • model.safetensors
    1.26 GB
    xet
    Rename adapter_model.safetensors to model.safetensors about 2 years ago
  • special_tokens_map.json
    437 Bytes
    theseed-v0.2 about 2 years ago
  • tokenizer.json
    1.8 MB
    theseed-v0.2 about 2 years ago
  • tokenizer.model
    493 kB
    xet
    theseed-v0.2 about 2 years ago
  • tokenizer_config.json
    1.46 kB
    Update tokenizer_config.json about 2 years ago