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Duplicated from  deepseek-ai/DeepSeek-V4-Flash-0731

Jiunsong
/
SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX

Text Generation
Transformers
Safetensors
English
Korean
deepseek_v4
deepseek-v4
mixture-of-experts
fp4
fp8
bf16
mixed-precision
quantized
long-context
1m-context
reasoning
tool-calling
uncensored
vllm
obliteratus
supertune
dgx-spark
8-bit precision
Model card Files Files and versions
xet
Community
1

Instructions to use Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX")
    model = AutoModelForCausalLM.from_pretrained("Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX
  • SGLang

    How to use Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX 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 "Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX" \
        --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": "Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX",
    		"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 "Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX" \
            --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": "Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX with Docker Model Runner:

    docker model run hf.co/Jiunsong/SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX
SuperDeepseek-V4-Flash-abliterated-MQ-2xDGX / repro
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  • 2 contributors
History: 5 commits
Jiunsong's picture
Jiunsong
Add sealed execution bundle manifest
8ed8bde verified 14 days ago
  • scripts
    Add reproduction scripts 14 days ago
  • bundle_manifest.json
    7.53 kB
    Add sealed execution bundle manifest 14 days ago
  • superdeepseek_v4_flash.yaml
    5.76 kB
    Add sealed two-node runtime configuration 14 days ago