Instructions to use KeisukeMiyamoto/lambda-1-160m-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KeisukeMiyamoto/lambda-1-160m-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="KeisukeMiyamoto/lambda-1-160m-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("KeisukeMiyamoto/lambda-1-160m-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use KeisukeMiyamoto/lambda-1-160m-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "KeisukeMiyamoto/lambda-1-160m-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KeisukeMiyamoto/lambda-1-160m-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/KeisukeMiyamoto/lambda-1-160m-base
- SGLang
How to use KeisukeMiyamoto/lambda-1-160m-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 "KeisukeMiyamoto/lambda-1-160m-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": "KeisukeMiyamoto/lambda-1-160m-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 "KeisukeMiyamoto/lambda-1-160m-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": "KeisukeMiyamoto/lambda-1-160m-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use KeisukeMiyamoto/lambda-1-160m-base with Docker Model Runner:
docker model run hf.co/KeisukeMiyamoto/lambda-1-160m-base
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README.md
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## Support Lambda
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### Donate
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You can support the project with a donation starting from $5 through Ko-fi. Your support helps cover GPU costs and allows me to continue developing larger models.
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<a href="https://ko-fi.com/lambda_llm">
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<img src="assets/support_me_on_kofi_badge_blue.png" alt="Support Lambda on Ko-fi" width="240">
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## Support Lambda
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Lambda is an open-source project for building small Japanese language models from scratch. As a student, I have funded this project with income from my part-time job, but the growing training costs are becoming difficult to cover.
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Your support helps cover GPU costs and develop larger models. Thank you for helping Lambda continue to grow.
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### Vast.ai
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Vast.ai offers affordable cloud GPUs for AI training. If you purchase credits through the link below, I receive 3% in GPU credits at no extra cost to you.
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https://cloud.vast.ai/?ref_id=521936
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### Ko-fi
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Support Lambda with a donation starting from $5.
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<a href="https://ko-fi.com/lambda_llm">
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<img src="assets/support_me_on_kofi_badge_blue.png" alt="Support Lambda on Ko-fi" width="240">
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