| --- |
| license: mit |
| library_name: peft |
| base_model: Qwen/Qwen3-4B |
| tags: |
| - astronomy |
| - spectroscopy |
| - multimodal |
| - desi |
| - lora |
| --- |
| |
| # AstroSpecLM |
|
|
| AstroSpecLM is a spectrum-grounded language model for DESI one-dimensional |
| spectra. This repository contains the paper-aligned rank-16 checkpoint. |
|
|
| ## Model components |
|
|
| - `llm_lora/`: rank-16 LoRA adapter for `Qwen/Qwen3-4B`. |
| - `projector.pt`: mapping from SpecMAE tokens to Qwen hidden states. |
| - `spectral_token_embeddings.pt`: learned spectral boundary-token embeddings. |
| - `spec_encoder/model.safetensors`: frozen SpecMAE spectrum encoder. |
| - `tokenizer/`: tokenizer files with the three spectral special tokens. |
| - `model_config.yaml`: inference architecture and paths. |
|
|
| The Qwen3-4B base weights are not redistributed here. They are loaded from the |
| upstream `Qwen/Qwen3-4B` repository. |
|
|
| ## Architecture |
|
|
| ```text |
| DESI spectrum -> frozen SpecMAE encoder -> projector -> Qwen3-4B + LoRA -> text |
| ``` |
|
|
| The spectrum input is a preprocessed flux vector of length 7,781. The encoder |
| uses patch size 20 and stride 10. The projector produces 130 spectral tokens. |
|
|
| ## Checkpoint |
|
|
| This is the best checkpoint from the one-epoch rank-16 SFT run: |
|
|
| - training step: 9,697 |
| - validation loss: 0.8958333147 |
| - LoRA rank / alpha: 16 / 32 |
|
|
| Use this checkpoint with the AstroSpecLM source release and pass the downloaded |
| model directory as `--adapter-dir`. After downloading, replace |
| `/absolute/path/to/AstroSpecLM` in `model_config.yaml` with the absolute local |
| path of the downloaded model directory. |
|
|
| ```bash |
| hf download sjh11/AstroSpecLM --local-dir /absolute/path/to/AstroSpecLM |
| |
| python3 scripts/chat.py \ |
| --config /absolute/path/to/AstroSpecLM/model_config.yaml \ |
| --adapter-dir /absolute/path/to/AstroSpecLM \ |
| --spectrum-npy /path/to/demo_flux.npy |
| ``` |
|
|
| ## Scope and limitations |
|
|
| This is a research checkpoint, not a general-purpose scientific measurement |
| pipeline. Its generated descriptions and inferred physical properties require |
| independent validation before scientific use. Training datasets and the Qwen |
| base model are governed by their respective licenses. |
|
|
