Text Generation
Transformers
Safetensors
Vietnamese
English
kent
ssm
state-space-model
recurrent
linear-time
frequency-domain
dct
swiglu
custom_code
fp16
base
Instructions to use Vi-LAB/KenT-300M-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vi-LAB/KenT-300M-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Vi-LAB/KenT-300M-Base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Vi-LAB/KenT-300M-Base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Vi-LAB/KenT-300M-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-300M-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-300M-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Vi-LAB/KenT-300M-Base
- SGLang
How to use Vi-LAB/KenT-300M-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-300M-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-300M-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-300M-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-300M-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Vi-LAB/KenT-300M-Base with Docker Model Runner:
docker model run hf.co/Vi-LAB/KenT-300M-Base
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KenT-300M: EMA memory with learned per-layer alpha, 1 WNN per layer, 24 layers, fp32 EMA
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KenT-300M: EMA memory with learned per-layer alpha, 1 WNN per layer, 24 layers
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Merge branch 'main' of https://huggingface.co/Vi-LAB/KenT-100M-Base
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