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Vi-LAB
/
KenT-1B-Base

Text Generation
Transformers
Safetensors
English
kent
ssm
state-space-model
recurrent
linear-time
frequency-domain
dct
mlp
swiglu
custom_code
fp16
base
Model card Files Files and versions
xet
Community

Instructions to use Vi-LAB/KenT-1B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Vi-LAB/KenT-1B-Base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="Vi-LAB/KenT-1B-Base", trust_remote_code=True)
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("Vi-LAB/KenT-1B-Base", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use Vi-LAB/KenT-1B-Base with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Vi-LAB/KenT-1B-Base"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Vi-LAB/KenT-1B-Base",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/Vi-LAB/KenT-1B-Base
  • SGLang

    How to use Vi-LAB/KenT-1B-Base 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 "Vi-LAB/KenT-1B-Base" \
        --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": "Vi-LAB/KenT-1B-Base",
    		"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 "Vi-LAB/KenT-1B-Base" \
            --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": "Vi-LAB/KenT-1B-Base",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use Vi-LAB/KenT-1B-Base with Docker Model Runner:

    docker model run hf.co/Vi-LAB/KenT-1B-Base
KenT-1B-Base
3.99 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 21 commits
KenteaKe11's picture
KenteaKe11
KenT-1B-Base: step 1400
c75bb82 verified 10 minutes ago
  • .gitattributes
    1.52 kB
    initial commit 3 days ago
  • .gitignore
    35 Bytes
    ignore about 9 hours ago
  • README.md
    5.71 kB
    Update README.md about 6 hours ago
  • config.json
    709 Bytes
    siu about 10 hours ago
  • generation_config.json
    297 Bytes
    fix 3 days ago
  • infer.py
    8.93 kB
    siu about 10 hours ago
  • model.py
    25.6 kB
    siu about 10 hours ago
  • model.safetensors
    3.99 GB
    xet
    KenT-1B-Base: step 1400 10 minutes ago
  • tokenizer.json
    3.56 MB
    add tokenizer file 3 days ago
  • tokenizer_config.json
    326 Bytes
    fix 3 days ago