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langleu/qmd-query-expansion-lfm2.5-1.2b-instruct-v1-verbose
qmd-query-expansion-lfm2.5-1.2b-instruct-v1-verbose is a text generation model from langleu. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as other.
LiquidAI/LFM2.5-1.2B-Instruct fine-tuned with LoRA for QMD query expansion using the v1-style verbose distillation data recipe. This repository contains the merged BF16 Transformers checkpoint at its root and QMD-read…
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From the Hugging Face model README
LiquidAI/LFM2.5-1.2B-Instruct fine-tuned with LoRA for QMD query expansion using the v1-style verbose distillation data recipe. This repository contains the merged BF16 Transformers checkpoint at its root and QMD-ready GGUF quantizations alongside it.
AutoModelForCausalLM.from_pretrained("langleu/qmd-query-expansion-lfm2.5-1.2b-instruct-v1-verbose", torch_dtype=torch.bfloat16).qmd-query-expansion-lfm2.5-1.2b-instruct-verbose-q5_k_m.ggufThe BF16 checkpoint is the unquantized merged fine-tune. The GGUF files are derived from that same merged checkpoint.
qmd-query-expansion-lfm2.5-1.2b-instruct-verbose-q5_k_m.gguf26a2e57d78c6bbd35da9cd720e09e4907df49c0b2003d4fe4beee24b21e2dfd1LiquidAI/LFM2.5-1.2B-Instruct868df74dd56ff8a0c2ac5dbf281690c2dbebe4c9tobil/qmd-query-expansion-trainb3f2387077f3f0be5cd83689242783bbda1d983fqmd-q5-scored/no_think Expand this search query: {query}
This variant emits a deliberately verbose seven-line expansion:
one hyde:, three lex:, and three vec: lines. It was not trained for
Query intent: or /only:* directives.
Each emitted line begins with lex:, vec:, or hyde:.
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-instruct-v1-verbose/qmd-query-expansion-lfm2.5-1.2b-instruct-verbose-q5_k_m.gguf"
qmd query --json --explain --no-rerank "docker container shutdown timeout"
The public historical query set was used as the source of
queries. Because it does not contain the unpublished labels used to train Tobil's
Qwen3 release, labels were reconstructed locally by teacher distillation from
tobil/qmd-query-expansion-1.7B
Q5_K_M. Accepted teacher outputs were quality-scored, deduplicated, and split
into 4,630 training and 516 untouched validation examples.
tobil/qmd-query-expansion-1.7B Q5_K_M| Format | Avg reward | Δ vs BF16 | Format compliance | Entity |
|---|---|---|---|---|
| BF16 | 97.70% | baseline | 100.00% | 100.00% |
| Q5_K_M | 97.39% | -0.31 pp | 99.42% | 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.
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. The verbose v1-style variant also discloses its Tobil Qwen3 teacher provenance above.