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Duplicated from  mobilint/EXAONE-Deep-2.4B

mobilint
/
EXAONE-Deep-2.4B-Batch16

Text Generation
Transformers
Safetensors
Mobilint
English
Korean
mobilint-exaone
conversational
custom_code
Model card Files Files and versions
xet
Community

Instructions to use mobilint/EXAONE-Deep-2.4B-Batch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mobilint/EXAONE-Deep-2.4B-Batch16 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="mobilint/EXAONE-Deep-2.4B-Batch16", trust_remote_code=True)
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("mobilint/EXAONE-Deep-2.4B-Batch16", trust_remote_code=True, dtype="auto")
  • Mobilint

    How to use mobilint/EXAONE-Deep-2.4B-Batch16 with Mobilint:

    # pip install mblt-model-zoo
    from mblt_model_zoo.vision import MBLT_Engine
    
    model = MBLT_Engine(
        model_cls="EXAONE-Deep-2.4B-Batch16",
        model_type="DEFAULT",
        model_path="",
        core_mode="global8",
    )
    
    try:
        image = model.preprocess("path/to/image.jpg")
        output = model(image)
        result = model.postprocess(output)
    finally:
        model.dispose()
    
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use mobilint/EXAONE-Deep-2.4B-Batch16 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "mobilint/EXAONE-Deep-2.4B-Batch16"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "mobilint/EXAONE-Deep-2.4B-Batch16",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/mobilint/EXAONE-Deep-2.4B-Batch16
  • SGLang

    How to use mobilint/EXAONE-Deep-2.4B-Batch16 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 "mobilint/EXAONE-Deep-2.4B-Batch16" \
        --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": "mobilint/EXAONE-Deep-2.4B-Batch16",
    		"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 "mobilint/EXAONE-Deep-2.4B-Batch16" \
            --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": "mobilint/EXAONE-Deep-2.4B-Batch16",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use mobilint/EXAONE-Deep-2.4B-Batch16 with Docker Model Runner:

    docker model run hf.co/mobilint/EXAONE-Deep-2.4B-Batch16
EXAONE-Deep-2.4B-Batch16
3.83 GB
Ctrl+K
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  • 2 contributors
History: 7 commits
lbs1163's picture
lbs1163
Update model card metadata
e9c58b9 verified 17 days ago
  • .gitattributes
    1.56 kB
    Duplicate from mobilint/EXAONE-Deep-2.4B 3 months ago
  • EXAONE-Deep-2.4B-Batch16-W8.mxq
    2.77 GB
    xet
    Upload EXAONE-Deep-2.4B-Batch16-W8.mxq to main 3 months ago
  • README.md
    762 Bytes
    Update model card metadata 17 days ago
  • config.json
    1.15 kB
    chore: update batch llm config about 2 months ago
  • generation_config.json
    223 Bytes
    Duplicate from mobilint/EXAONE-Deep-2.4B 3 months ago
  • merges.txt
    1.22 MB
    Duplicate from mobilint/EXAONE-Deep-2.4B 3 months ago
  • model.safetensors
    1.05 GB
    xet
    Duplicate from mobilint/EXAONE-Deep-2.4B 3 months ago
  • proxy_exaone.py
    486 Bytes
    Duplicate from mobilint/EXAONE-Deep-2.4B 3 months ago
  • special_tokens_map.json
    563 Bytes
    Duplicate from mobilint/EXAONE-Deep-2.4B 3 months ago
  • tokenizer.json
    4.96 MB
    Duplicate from mobilint/EXAONE-Deep-2.4B 3 months ago
  • tokenizer_config.json
    70.9 kB
    Duplicate from mobilint/EXAONE-Deep-2.4B 3 months ago
  • vocab.json
    1.93 MB
    Duplicate from mobilint/EXAONE-Deep-2.4B 3 months ago