langleu/qmd-query-expansion-lfm2.5-1.2b-base-v2
LiquidAI/LFM2.5-1.2B-Base fine-tuned with LoRA for QMD query expansion using the v2 data recipe. This repository contains the merged BF16 Transformers checkpoint at its root and QMD-ready GGUF quantizations alongside it.
Repository formats
- Merged BF16 Transformers checkpoint: load the repository directly with
AutoModelForCausalLM.from_pretrained("langleu/qmd-query-expansion-lfm2.5-1.2b-base-v2", torch_dtype=torch.bfloat16). - GGUF for QMD/llama.cpp:
qmd-query-expansion-lfm2.5-1.2b-q8_0.gguf,qmd-query-expansion-lfm2.5-1.2b-q5_k_m.gguf,qmd-query-expansion-lfm2.5-1.2b-q4_k_m.gguf
The BF16 checkpoint is the unquantized merged fine-tune. The GGUF files are derived from that same merged checkpoint.
Artifact validated by this publishing invocation
- File:
qmd-query-expansion-lfm2.5-1.2b-q5_k_m.gguf - Kind: GGUF
- Size: 843,354,048 bytes
- SHA-256:
c51ccefa421b77cef13999049e520f807b58158057449784a3c9669e31a08963 - Base model:
LiquidAI/LFM2.5-1.2B-Base - Base revision:
f6a5d174bc3e52bd0df245d69133f9930b4828d8 - Dataset:
tobil/qmd-query-expansion-train-v2 - Dataset revision:
9b9c3dd41a11209f3ce907908f9b865f0ead415e - Configured release quantizations: Q8_0, Q5_K_M, Q4_K_M
- Evaluation report:
q5_k_m
Prompt and behavior
/no_think Expand this search query: {query}
This variant supports the production v2 QMD behavior:
an optional Query intent: line and /only:lex, /only:vec, and /only:hyde
directives.
Each emitted line begins with lex:, vec:, or hyde:.
Use with QMD
The Transformers checkpoint is not loaded by QMD directly; select one of the GGUF files.
For a private repository, authenticate once with hf auth login, or set
HF_TOKEN. QMD's node-llama-cpp downloader reads the cached Hugging Face
token from ~/.cache/huggingface/token by default.
export QMD_GENERATE_MODEL="hf:langleu/qmd-query-expansion-lfm2.5-1.2b-base-v2/qmd-query-expansion-lfm2.5-1.2b-q5_k_m.gguf"
qmd query --json --explain --no-rerank "docker container shutdown timeout"
Training-data provenance
Training records were rebuilt from the pinned dataset's
messages field with the target LFM2.5 tokenizer. The dataset's preformatted
Qwen text was not used. Completion-only loss masked the user prompt.
Validation
- Average QMD reward: 95.17%
- Format compliance: 100.00%
- Entity preservation: 98.31%
/only:*behavior: 100.00%- Hard failures: 0
BF16 and GGUF comparison
| Format | Avg reward | Δ vs BF16 | Format compliance | Entity | /only:* |
|---|---|---|---|---|---|
| BF16 | 95.13% | baseline | 100.00% | 100.00% | 100.00% |
| Q8_0 | 94.91% | -0.22 pp | 99.68% | 96.61% | 98.85% |
| Q5_K_M | 95.17% | +0.04 pp | 100.00% | 98.31% | 100.00% |
| Q4_K_M | 94.76% | -0.37 pp | 100.00% | 98.31% | 100.00% |
Quality changes are reported in percentage points (pp), not relative percent. Small positive GGUF deltas can occur because sampled generation is not bit-for-bit deterministic.
Speed percentages are intentionally not reported. BF16 was measured with batched Transformers inference, while QMD runs GGUF through llama.cpp one query at a time. Their observed throughput and latency are useful operational measurements, but dividing them would not be an apples-to-apples speedup.
Credits
- Liquid AI for LFM2.5 and the LFM Open License v1.0.
- Tobi for QMD, the QMD query-expansion datasets, evaluation/scoring design, and the Qwen3 query-expansion model.
- OrcsRise for the earlier LFM2 QMD fine-tuning work that informed the LFM target-module recipe.
- QMD, TRL, PEFT, and llama.cpp.
Licensing and dataset notice
This derivative is governed by the LFM Open License v1.0. The included
LICENSE must be retained, including its attribution and commercial-use terms.
The upstream QMD dataset card did not declare an explicit dataset license at the pinned revision. This repository records that fact and does not imply that a license was granted. Users and redistributors are responsible for confirming that their use is authorized.