Instructions to use MK0727/lambda-160m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MK0727/lambda-160m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MK0727/lambda-160m", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("MK0727/lambda-160m", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use MK0727/lambda-160m with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MK0727/lambda-160m" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MK0727/lambda-160m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/MK0727/lambda-160m
- SGLang
How to use MK0727/lambda-160m 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 "MK0727/lambda-160m" \ --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": "MK0727/lambda-160m", "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 "MK0727/lambda-160m" \ --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": "MK0727/lambda-160m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use MK0727/lambda-160m with Docker Model Runner:
docker model run hf.co/MK0727/lambda-160m
File size: 472 Bytes
134df9b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"backend": "tokenizers",
"bos_token": "|<bos>|",
"cls_token": "|<cls>|",
"eos_token": "|<eos>|",
"extra_special_tokens": [
"|<system>|",
"|<user>|",
"|<assistant>|",
"|<thinking>|",
"|<end_of_thinking>|",
"|<end_of_turn>|"
],
"mask_token": "|<mask>|",
"model_max_length": 1000000000000000019884624838656,
"pad_token": "|<pad>|",
"sep_token": "|<sep>|",
"tokenizer_class": "TokenizersBackend",
"unk_token": "|<unknown>|"
}
|