| | --- |
| | license: apache-2.0 |
| | language: |
| | - en |
| | pipeline_tag: text-generation |
| | tags: |
| | - reasoning |
| | - math |
| | - coding |
| | - distillation |
| | - small-model |
| | --- |
| | |
| | # DeepBrainz R1-0.6B |
| |
|
| | **DeepBrainz R1-0.6B** 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 emphasizes **structured reasoning**, **stepwise problem decomposition**, and **stable generation behavior**, making it well-suited for research, education, and lightweight deployment scenarios. |
| |
|
| | --- |
| |
|
| | ## 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 |
| |
|
| | --- |
| |
|
| | ## 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. |
| |
|
| | --- |
| |
|
| | ## Usage |
| |
|
| | ```python |
| | from transformers import AutoModelForCausalLM, AutoTokenizer |
| | |
| | model_id = "DeepBrainz/deepbrainz-r1-0.6b" |
| | |
| | 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)) |
| | ``` |
| |
|
| | --- |
| |
|
| | ## Training & Alignment |
| |
|
| | R1-0.6B was trained using modern post-training techniques emphasizing reasoning quality and generation stability. |
| | Specific training details are intentionally abstracted in this public-facing release. |
| |
|
| | --- |
| |
|
| | ## Limitations |
| |
|
| | Performance is constrained by model size |
| | Not optimized for open-ended conversational chat |
| | Best for short-to-medium complexity reasoning tasks |
| |
|
| | --- |
| |
|
| | ## License |
| |
|
| | Apache 2.0 |
| |
|
| | --- |
| |
|
| | ## 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. |
| |
|
