joshycodes/qwen3-32b-fve-flouranchor-s0
joshycodes/qwen3-32b-fve-flouranchor-s0 is a 32 billion parameter Qwen3-based language model that underwent continued pretraining on a self-authored corpus. This model was trained for one epoch on 7,142,274 tokens across 7,800 documents, with the corpus generated by the model itself to inform its next iteration. It represents a research checkpoint focused on exploring self-authored data for continued pretraining, and is not yet evaluated for capability, alignment, or identity.
Loading preview...
Overview
joshycodes/qwen3-32b-fve-flouranchor-s0 is a 32 billion parameter model derived from the Qwen3-32B architecture. This model is a research checkpoint focused on an experimental continued pretraining methodology. It was trained on a unique corpus that the model itself authored, designed to inform the development of its subsequent versions.
Key Characteristics
- Self-Authored Corpus: The model underwent continued pretraining on a corpus it generated, totaling 7,142,274 tokens from 7,800 documents. This corpus was created based on the model's understanding of its own character and the SDF framework.
- Continued Pretraining: The training involved a full-weights update over one epoch with a learning rate of 1e-05.
- Research Focus: This model is explicitly a research checkpoint, exploring novel methods of self-referential data generation for model improvement.
Important Considerations
- Unevaluated Status: The model has not yet been evaluated for its general capabilities, alignment, or identity. Users should be aware that its performance characteristics are currently unknown.
- Do Not Deploy: Due to its experimental nature and lack of evaluation, the developers explicitly state that this model should not be deployed in production environments.