v0.0.3 trajectory — in-progress release (cheap-path 500-step v0.1.x AV)

In-progress trajectory release. Adapter weights for each saved checkpoint of the cheap-path 500-step v0.1.x AV SFT run, attached as release assets. New checkpoints land every ~2.5 hours of GPU time as training proceeds. Final v0.0.3 release tag with the complete trajectory + H14-style trend evaluation will land once training completes (~2026-05-14).

What's attached

Each adapter_model_step_XXXXXX.safetensors is a LoRA adapter from that checkpoint. Pair with the v0.0.1 AR (Solshine/gemma-4-e2b-nla-L23-ar-v0_0_1) for round-trip eval at that training scale.

For per-checkpoint metadata (adapter_config.json, nla_meta.yaml, README), see trajectory/ in the repo source.

Currently attached

• adapter_model_step_000050.safetensors (387 MB) — loss 2.38 at step 50
• adapter_model_step_000100.safetensors (387 MB) — loss 2.24 at step 100

(More will be added as checkpoints save.)

Mirror

Same checkpoints are also on HuggingFace at Solshine/gemma-4-e2b-nla-L23-av-v0_1_x-trajectory. Use whichever mirror is faster for you.

Hardware-constraint disclosure

Same disclaimers as v0.0.2 apply: this is a small-model variant pushed to the limit of a 4 GB consumer GPU. See main README for the full discussion of AR content-blindness and the empirical ceiling at v0.0.x compute scale.