Blake Haiku 1 is an instruct LLM consisting of 0.6B parameters trained to talk in a human conversational manner. It was trained without support for reasoning nor tool-calling.
The model was LoRA fine-tuned with Qwen/Qwen3-0.6B as base model.

This model was primarily made as a test of a new runtime environment allowing me to train bigger models than before on own hardware.
Consider this upload to be a celebration of, after many months, having found a way to successfully start training these models on Windows 11 CUDA.

Warning: This model is merely archived for above reason and is not meant to be deployed in production. Training data was minimal.
There will likely not be a Blake Haiku 2.

Blake Haiku 1 uses the ChatML format, e.g.:

We recommend using the following system prompt:

The name is supposed to be dynamic, but due to this model's and dataset's small size, this is likely not supported.

The assistant response has the following format:

Each line is supposed to be a new "message" in a conversation, mimicking humans using traditional chatting platforms (e.g. Discord, where you can send multiple messages before someone responds).

Note that the <think>...</think> tags are always empty, as this model was not trained on reasoning data.