model: add fangxq/XYZ-embedding

mteb/models/xyz_models.py

@@ -0,0 +1,42 @@
+from __future__ import annotations
+
+from mteb.model_meta import ModelMeta, sentence_transformers_loader
+
+xyz_zh_datasets = {
+    "BQ": ["train"],
+    "LCQMC": ["train"],
+    "PAWSX": ["train"],
+    "STS-B": ["train"],
+    "DuRetrieval": ["train"],
+    "AFQMC": ["train"],
+    "Cmnli": ["train"],
+    "Ocnli": ["train"],
+    "T2Retrieval": ["train"],
+    "T2Reranking": ["train"],
+    "MMarcoReranking": ["train"],
+    "CMedQAv2-reranking": ["train"],
+    "Covid-News":"NCPPolicies_train",
+    "cMedQA":"https://github.com/zhangsheng93/cMedQA",
+    "Multi-CPR":"http://github.com/Alibaba-NLP/Multi-CPR",
+    "retrieval_data_llm":"https://huggingface.co/datasets/infgrad/retrieval_data_llm",
+    "Huatuo26M-Lite":"https://huggingface.co/datasets/FreedomIntelligence/Huatuo26M-Lite"}
+
+xyz_embedding = ModelMeta(
+    name="fangxq/XYZ-embedding",
+    languages=["zho-Hans"],
+    loader=sentence_transformers_loader,
+    open_weights=False,
+    revision="4004120220b99baea764a1d3508427248ac3bccf",
+    release_date="2024-09-13",
+    n_parameters=326000000,
+    memory_usage_mb=1242,
+    max_tokens=512,
+    embed_dim=768,
+    license="mit",
+    similarity_fn_name="cosine",
+    framework=["Sentence Transformers"],
+    reference="https://huggingface.co/fangxq/XYZ-embedding",
+    use_instructions=False,
+    training_datasets= {**xyz_zh_datasets},
+    public_training_code=None,
+    public_training_data=None,)