Phi-4-mini Instruct β Cascadia int4 shards
Pre-exported Cascadia inference shards for
microsoft/Phi-4-mini-instruct, so operators can deploy without running an export themselves.
These are OpenVINO IR artifacts for Cascadia's ov-runtime engine. They are not
loadable by transformers β see Using these below.
Contents
| Preset | Path | Stages | Quant | Size |
|---|---|---|---|---|
1 |
int4/stages-1 |
1 | int4 | 1.9 GB |
int4/stages-1/
pipeline_config.json # model geometry: layers, heads, rope, arch tag
stage_0/
openvino_model.xml # IR graph
openvino_model.bin # int4 weights
stage_config.json # layer_start, layer_end, has_embed, has_head
tokenizer/ # tokenizer.json + configs
cascadia.json at the repo root is the machine-readable index (sizes, checksums,
export version) that Cascadia's model registry reads.
Using these
hf download communitylabs/cascadia-phi-4-mini-int4 --local-dir ./phi-4-mini
cascadia worker --model ./phi-4-mini/int4/stages-1 --engine ov-runtime
The worker takes a local path, never a HuggingFace id β Cascadia workers never download or convert models at serve time.
Provenance
Exported with Cascadia's tools/export_shards.py, export_version: v5_canonical_inputs.
| Source | microsoft/Phi-4-mini-instruct |
| Layers | 32 |
| Hidden size | 3072 |
| Attention heads | 24 (8 KV) |
| Vocab | 200064 |
| RoPE theta | 10000.0 (partial rotary factor 0.75) |
| Quantization | int4 (NNCF, group size 128) |
Quantization is lossy. For anything quality-sensitive, benchmark against the source model rather than assuming parity.
License
MIT, inherited from microsoft/Phi-4-mini-instruct.
These shards are a derivative work; the upstream license and its terms apply.
Model tree for communitylabs/cascadia-phi-4-mini-int4
Base model
microsoft/Phi-4-mini-instruct