Text Generation
MLX
Safetensors
English
lemonseed
mixture-of-experts
gated-deltanet
mixture-of-depths
rocm
base-model
Instructions to use lemonade-sdk/lemonseed-1.5b-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use lemonade-sdk/lemonseed-1.5b-base with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("lemonade-sdk/lemonseed-1.5b-base") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use lemonade-sdk/lemonseed-1.5b-base with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "lemonade-sdk/lemonseed-1.5b-base" --prompt "Once upon a time"
- Atomic Chat
Reference LSE (Lemon Seed Engine) as the primary runtime
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example_generate.py
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"""LemonSeed 1.5B — minimal generation template.
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LemonSeed is a custom hybrid (Gated-DeltaNet + attention + MoE + Mixture-of-Depths)
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architecture and is NOT loadable via `transformers`.
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pip install mlx fastokens huggingface_hub
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git clone https://github.com/Geramy/lemonseed-docs && cd lemonseed
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"""LemonSeed 1.5B — minimal generation template.
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LemonSeed is a custom hybrid (Gated-DeltaNet + attention + MoE + Mixture-of-Depths)
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architecture and is NOT loadable via `transformers`.
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Primary engine (C++/ROCm): https://github.com/Geramy/LSE
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Reference docs: https://github.com/Geramy/lemonseed-docs
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This file is the simple MLX reference path (needs the lemonseed Python model code).
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pip install mlx fastokens huggingface_hub
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git clone https://github.com/Geramy/lemonseed-docs && cd lemonseed
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