DeepBrainz-R1-2B-16K

DeepBrainz-R1-2B-16K is a compact, high-performance reasoning model engineered by DeepBrainz AI & Labs. Designed for efficiency and scalability, it specializes in structured chain-of-thought reasoning, mathematical problem solving, and logical analysis.

This model is part of the DeepBrainz-R1 Series, built to deliver frontier-class reasoning capabilities in cost-effective parameter sizes.

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🚀 Model Highlights

• Parameter Count: ~2B
• Context Window: 16,384 tokens
• Specialization: STEM Reasoning, Logic, Code Analysis
• Architecture: Optimized Dense Transformer (Qwen2.5/3 Compatible)
• Deployment: Ready for vLLM, TGI, and local inference

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🎯 Intended Use Cases

• Agentic Workflows: Reliability in multi-step planning tasks.
• Math & Science: Solving complex word problems and equations.
• Code Generation: Writing and debugging algorithms.
• Structured Data Extraction: Parsing and reasoning over unstructured text.

Note: This is a post-trained reasoning variant intended for evaluation and experimentation.
It is not production-validated and is not optimized for open-ended conversational chat.

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💻 Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "DeepBrainz/DeepBrainz-R1-2B-16K"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype="bfloat16",
    device_map="auto"
)

prompt = "Analyze the time complexity of the following algorithm:"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

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🏗️ Technical Summary

This model has undergone post-training to enhance reasoning behavior and robustness under agentic workloads.

Detailed post-training recipes and dataset compositions are not fully disclosed.

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🛡️ Limitations & Safety

While this model demonstrates strong reasoning capabilities, it may still produce inaccurate information ("hallucinations"). Users should implement appropriate guardrails for production deployments.

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📜 License

This model is released under the Apache 2.0 license, allowing for academic and commercial use.

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DeepBrainz AI & Labs
Advancing General Intelligence through Scalable Reasoning