Create README.md

README.md

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+---
+language:
+- multilingual
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen3-0.6B
+pipeline_tag: text-generation
+---
+
+# Qwen3 mHC 
+
+This checkpoint is a Manifold-Constrained Hyper-Connections (mHC) V2 variant of Qwen/Qwen3-0.6B, trained for 30k steps in a parity-mixed setup. It is intended for research on residual stream mixing and hyper-connection behavior.
+
+## Model Description
+
+- **Base model:** Qwen/Qwen3-0.6B
+- **Architecture:** Qwen3 with mHC V2 hyper-connections (stream-mixing)
+- **Checkpoint:** 30,000 steps
+- **Language(s):** Multilingual (see data notes)
+- **License:** Apache-2.0 (inherits base model license)
+
+## Intended Use
+
+- Research on mHC V2 hyper-connections and residual stream mixing
+- Fine-tuning or continued training experiments
+- Analysis of stream specialization behavior
+
+## Out-of-Scope Use
+
+- Safety-critical or medical decision-making systems
+- High-stakes automated decision-making without human oversight
+
+## Training Data
+
+This checkpoint was trained on multilingual pretokenized datasets, primarily Sangraha shards. The data is prepacked into train/validation splits or shard layouts. Exact dataset composition and filtering are not fully documented here.
+
+## Training Procedure
+
+- Converted from a Qwen3 base checkpoint into an mHC V2 model.
+- Trained for 30k steps in a parity-mixed run.
+- Uses Sinkhorn-based projection for residual mixing stability.
+
+## Evaluation
+
+No formal benchmarks are bundled with this checkpoint. If you evaluate this model, please report the setup, prompts, decoding parameters, and comparison baselines.