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LDCC
/
LDCC-SOLAR-10.7B

Text Generation
Transformers
Safetensors
Korean
llama
text-generation-inference
Model card Files Files and versions
xet
Community
6

Instructions to use LDCC/LDCC-SOLAR-10.7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use LDCC/LDCC-SOLAR-10.7B with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="LDCC/LDCC-SOLAR-10.7B")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("LDCC/LDCC-SOLAR-10.7B")
    model = AutoModelForCausalLM.from_pretrained("LDCC/LDCC-SOLAR-10.7B")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use LDCC/LDCC-SOLAR-10.7B with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "LDCC/LDCC-SOLAR-10.7B"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "LDCC/LDCC-SOLAR-10.7B",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/LDCC/LDCC-SOLAR-10.7B
  • SGLang

    How to use LDCC/LDCC-SOLAR-10.7B 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 "LDCC/LDCC-SOLAR-10.7B" \
        --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": "LDCC/LDCC-SOLAR-10.7B",
    		"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 "LDCC/LDCC-SOLAR-10.7B" \
            --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": "LDCC/LDCC-SOLAR-10.7B",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use LDCC/LDCC-SOLAR-10.7B with Docker Model Runner:

    docker model run hf.co/LDCC/LDCC-SOLAR-10.7B
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ํ•™์Šต์— ํ™œ์šฉ๋œ ๋ฐ์ดํ„ฐ ๋ฌธ์˜

2
#6 opened about 2 years ago by
RoiandDae

Adding Evaluation Results

#5 opened about 2 years ago by
leaderboard-pr-bot

๋‹ต๋ณ€ ๊ธธ์ด๊ด€๋ จํ•ด์„œ ์—ฌ์ญค๋ณผ๊ป˜์žˆ์Šต๋‹ˆ๋‹ค!

2
#4 opened over 2 years ago by
HIMINSU

๋ฆฌ๋“œ๋ฏธ์— ๋‚จ๊ฒจ๋‘์‹  ํ† ํฌ๋‚˜์ด์ € ๊ด€๋ จ ์ด์Šˆ๊ฐ€ ๊ถ๊ธˆํ•ด์„œ ์˜ฌ๋ฆฝ๋‹ˆ๋‹ค.

3
#3 opened over 2 years ago by
StatPan
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