| --- |
| license: apache-2.0 |
| language: |
| - en |
| pipeline_tag: text-generation |
| tags: |
| - deepbrainz |
| - reasoning |
| - mathematics |
| - code |
| - enterprise |
| - 0.6b |
| library_name: transformers |
| --- |
| |
| # DeepBrainz-R1-0.6B-16K |
|
|
| **DeepBrainz-R1-0.6B-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. |
|
|
| --- |
|
|
| ## 🚀 Model Highlights |
|
|
| - **Parameter Count:** ~0.6B |
| - **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 |
|
|
| --- |
|
|
| ## 🎯 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. |
|
|
| --- |
|
|
| ## 💻 Usage |
|
|
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model_id = "DeepBrainz/DeepBrainz-R1-0.6B-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)) |
| ``` |
|
|
| --- |
|
|
| 🏗️ 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. |
|
|
| --- |
|
|
| ## 🛡️ Limitations & Safety |
|
|
| While this model demonstrates strong reasoning capabilities, it may still produce inaccurate information ("hallucinations"). Users should implement appropriate guardrails for production deployments. |
|
|
| --- |
|
|
| ## 📜 License |
|
|
| This model is released under the **Apache 2.0** license, allowing for academic and commercial use. |
|
|
| --- |
|
|
| <div align="center"> |
| <b>DeepBrainz AI & Labs</b><br> |
| <i>Advancing General Intelligence through Scalable Reasoning</i> |
| </div> |
|
|
