DeepBrainz-R1-0.6B-Exp

DeepBrainz-R1-0.6B-Exp is a compact, reasoning-focused language model designed for efficient problem-solving in mathematics, logic, and code-related tasks.

Despite its small size, R1-0.6B-Exp emphasizes experimental structured reasoning, stepwise problem decomposition, and stable generation behavior, making it well-suited for research, education, and lightweight deployment scenarios.

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Model Highlights

• Compact 0.6B parameter model optimized for efficiency
• Strong focus on reasoning-oriented tasks
• Stable long-form generation for its size class
• Compatible with standard Hugging Face inference tooling

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Intended Use

This model is intended for:

• Research and experimentation in reasoning-focused LLMs
• Educational use and demonstrations
• Lightweight inference environments
• Building blocks for agentic or tool-augmented systems

It is not intended as a general-purpose chat replacement for larger frontier models.

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Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "DeepBrainz/DeepBrainz-R1-0.6B-Exp"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

prompt = "Solve step by step: If x + 3 = 7, what is x?"
inputs = tokenizer(prompt, return_tensors="pt")

outputs = model.generate(
    **inputs,
    max_new_tokens=256,
    temperature=0.6,
    top_p=0.95,
    do_sample=True,
)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

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Training & Alignment

R1-0.6B-Exp was trained using modern post-training techniques emphasizing reasoning quality and generation stability. Specific training details are intentionally abstracted in this public-facing release.

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Limitations

Performance is constrained by model size Not optimized for open-ended conversational chat Best for short-to-medium complexity reasoning tasks

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License

Apache 2.0

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About DeepBrainz

DeepBrainz builds reasoning-first AI systems focused on efficiency, structure, and real-world problem-solving.

More evaluations and updates will follow in future releases.