model: add pixie_models

mteb/models/model_implementations/pixie_models.py

@@ -0,0 +1,56 @@
+from mteb.models.model_implementations.arctic_models import (
+    ARCTIC_V2_CITATION,
+    LANGUAGES_V2_0,
+    arctic_v2_training_datasets,
+)
+from mteb.models.model_meta import (
+    ModelMeta,
+    ScoringFunction,
+)
+from mteb.models.sentence_transformer_wrapper import sentence_transformers_loader
+
+PIXIE_RUNE_V1_CITATION = """@misc{TelePIX-PIXIE-Rune-v1.0,
+  title        = {PIXIE-Rune-v1.0},
+  author       = {TelePIX AI Research Team and Bongmin Kim},
+  year         = {2026},
+  howpublished = {Hugging Face model card},
+  url          = {https://huggingface.co/telepix/PIXIE-Rune-v1.0}
+}"""
+
+PIXIE_RUNE_V1_PROMPTS = {
+    "query": "query: ",
+    "document": "",
+}
+
+# it is further fine-tuned on TelePIX proprietary IR data (not public).
+pixie_rune_v1_training_datasets = set(arctic_v2_training_datasets) | {
+    "TelePIX-Proprietary-IR-Triplets",
+}
+
+pixie_rune_v1_0 = ModelMeta(
+    loader=sentence_transformers_loader,
+    loader_kwargs={
+        "model_prompts": PIXIE_RUNE_V1_PROMPTS,
+    },
+    name="telepix/PIXIE-Rune-v1.0",
+    model_type=["dense"],
+    revision="b2486496da71191626666a88f9bfec844933a134",
+    release_date="2026-01-15",
+    languages=LANGUAGES_V2_0,
+    open_weights=True,
+    framework=["Sentence Transformers", "PyTorch", "safetensors"],
+    n_parameters=567754752,
+    memory_usage_mb=2166,
+    max_tokens=6144,
+    embed_dim=1024,
+    license="apache-2.0",
+    reference="https://huggingface.co/telepix/PIXIE-Rune-v1.0",
+    similarity_fn_name=ScoringFunction.COSINE,
+    use_instructions=True,
+    adapted_from="Snowflake/snowflake-arctic-embed-l-v2.0",
+    superseded_by=None,
+    public_training_code=None,
+    public_training_data=None,
+    training_datasets=pixie_rune_v1_training_datasets,
+    citation=PIXIE_RUNE_V1_CITATION + "\n\n" + ARCTIC_V2_CITATION,
+)