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README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+language:
+- pt
+library_name: transformers
+---
+
+**Axion1.5-0.3B-Base**
+
+🧠 Axion1.5-0.3B-Base is a base language model with approximately 300 million parameters, trained purely for next-token prediction.
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+No instruction tuning.
+No reinforcement learning.
+No forced reasoning chains.
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+Just raw language modeling.
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+This model exists with a clear goal: to act as a clean, transparent baseline for future experiments focused on explicit reasoning and structured thinking.
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+What this model is
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+A foundation / base model
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+Trained only with next-token prediction
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+Not optimized for chat or instruction-following
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+Designed as a reference point for research and comparison
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+A functional “blank mind” before reasoning specialization
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+What this model is not
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+❌ Not a chatbot
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+❌ Not instruction-tuned
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+❌ Not aligned for safety or helpfulness
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+❌ Not optimized for long conversations
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+❌ Not a reasoning model (yet)
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+If you are looking for a model that follows instructions or explains its thoughts, this is not it.
+
+Why release a base model?
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+Releasing the base model publicly allows:
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+Transparent evaluation of raw language modeling quality
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+Fair comparison with future Axion reasoning variants
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+Reproducibility and honest benchmarking
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+A clear separation between language competence and reasoning behavior
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+Many projects hide their base models.
+Axion does the opposite.
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+Intended use
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+Research and experimentation
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+Fine-tuning for instruction-following or reasoning tasks
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+Studying the effects of reasoning-oriented datasets
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+Serving as a backbone for Axion1.5-Reasoning variants
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+Limitations
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+Because this model is trained only for next-token prediction:
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+It may produce incoherent or incomplete responses
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+It does not reliably follow instructions
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+It does not reason step-by-step
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+It may hallucinate or contradict itself
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+These limitations are expected and acknowledged.
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+Future work
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+This release is part of a broader project:
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+Axion1.5-Reasoning – fine-tuned for structured reasoning
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+Axion-Critic – models focused on evaluation and self-critique
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+Experiments with short, verifiable reasoning traces
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+The base model will remain unchanged to preserve its value as a reference.
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+Philosophy
+
+Scale is not intelligence.
+Structure matters.
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+Axion explores whether smaller models, trained with the right constraints, can develop more meaningful reasoning behaviors.
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+This is an experiment.
+And experiments are allowed to fail.
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+Acknowledgements
+
+Created as an independent research project focused on understanding how reasoning emerges in language models.