diff --git a/mteb/models/arctic_models.py b/mteb/models/arctic_models.py
index 5f3d41a97..26af9c8cc 100644
--- a/mteb/models/arctic_models.py
+++ b/mteb/models/arctic_models.py
@@ -5,7 +5,7 @@
 from mteb.model_meta import ModelMeta, sentence_transformers_loader
 
 arctic_m_v1_5 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="Snowflake/snowflake-arctic-embed-m-v1.5",
         revision="97eab2e17fcb7ccb8bb94d6e547898fa1a6a0f47",
diff --git a/mteb/models/bge_models.py b/mteb/models/bge_models.py
index 5ab429479..b643b4dfb 100644
--- a/mteb/models/bge_models.py
+++ b/mteb/models/bge_models.py
@@ -7,7 +7,7 @@
 model_prompts = {"query": "Represent this sentence for searching relevant passages: "}
 
 bge_small_en_v1_5 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="BAAI/bge-small-en-v1.5",
         revision="5c38ec7c405ec4b44b94cc5a9bb96e735b38267a",
@@ -30,7 +30,7 @@
 )
 
 bge_base_en_v1_5 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="BAAI/bge-base-en-v1.5",
         revision="a5beb1e3e68b9ab74eb54cfd186867f64f240e1a",
@@ -53,7 +53,7 @@
 )
 
 bge_large_en_v1_5 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="BAAI/bge-large-en-v1.5",
         revision="d4aa6901d3a41ba39fb536a557fa166f842b0e09",
diff --git a/mteb/models/cohere_models.py b/mteb/models/cohere_models.py
index 26eb5e92e..b41043301 100644
--- a/mteb/models/cohere_models.py
+++ b/mteb/models/cohere_models.py
@@ -74,7 +74,7 @@ def encode(
 }
 
 cohere_mult_3 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         CohereTextEmbeddingModel,
         model_name="embed-multilingual-v3.0",
         model_prompts=model_prompts,
@@ -95,7 +95,7 @@ def encode(
 )
 
 cohere_eng_3 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         CohereTextEmbeddingModel,
         model_name="embed-multilingual-v3.0",
         model_prompts=model_prompts,
diff --git a/mteb/models/e5_instruct.py b/mteb/models/e5_instruct.py
index 5d5b1f3ad..f26d78ed6 100644
--- a/mteb/models/e5_instruct.py
+++ b/mteb/models/e5_instruct.py
@@ -12,15 +12,14 @@
 MISTRAL_LANGUAGES = ["eng_Latn", "fra_Latn", "deu_Latn", "ita_Latn", "spa_Latn"]
 
 
-def e5_instruction(instruction: str) -> str:
-    return f"Instruct: {instruction}\nQuery: "
+E5_INSTRUCTION = "Instruct: {instruction}\nQuery: "
 
 
 e5_instruct = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         instruct_wrapper,
         model_name_or_path="intfloat/multilingual-e5-large-instruct",
-        instruction_template=e5_instruction,
+        instruction_template=E5_INSTRUCTION,
         attn="cccc",
         pooling_method="mean",
         mode="embedding",
@@ -44,10 +43,10 @@ def e5_instruction(instruction: str) -> str:
 )
 
 e5_mistral = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         instruct_wrapper,
         model_name_or_path="intfloat/e5-mistral-7b-instruct",
-        instruction_template=e5_instruction,
+        instruction_template=E5_INSTRUCTION,
         attn="cccc",
         pooling_method="lasttoken",
         mode="embedding",
diff --git a/mteb/models/e5_models.py b/mteb/models/e5_models.py
index 612130ed6..943c46870 100644
--- a/mteb/models/e5_models.py
+++ b/mteb/models/e5_models.py
@@ -114,7 +114,7 @@
 }
 
 e5_mult_small = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="intfloat/multilingual-e5-small",
         revision="fd1525a9fd15316a2d503bf26ab031a61d056e98",
@@ -137,7 +137,7 @@
 )
 
 e5_mult_base = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="intfloat/multilingual-e5-base",
         model_prompts=model_prompts,
@@ -159,7 +159,7 @@
 )
 
 e5_mult_large = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="intfloat/multilingual-e5-large",
         revision="ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb",
@@ -182,7 +182,7 @@
 )
 
 e5_eng_small_v2 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="intfloat/e5-small-v2",
         model_prompts=model_prompts,
@@ -204,7 +204,7 @@
 )
 
 e5_eng_small = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="intfloat/e5-small",
         revision="e272f3049e853b47cb5ca3952268c6662abda68f",
@@ -227,7 +227,7 @@
 )
 
 e5_eng_base_v2 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="intfloat/e5-base-v2",
         revision="1c644c92ad3ba1efdad3f1451a637716616a20e8",
@@ -250,7 +250,7 @@
 )
 
 e5_eng_large_v2 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="intfloat/e5-large-v2",
         revision="b322e09026e4ea05f42beadf4d661fb4e101d311",
diff --git a/mteb/models/google_models.py b/mteb/models/google_models.py
index 688680abc..8066599b0 100644
--- a/mteb/models/google_models.py
+++ b/mteb/models/google_models.py
@@ -78,7 +78,7 @@ def encode(
 
 name = "text-embedding-004"
 google_emb_004 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         GoogleTextEmbeddingModel,
         model_name=name,
         model_prompts={
diff --git a/mteb/models/gritlm_models.py b/mteb/models/gritlm_models.py
index b1c4882bc..1e9c85eb8 100644
--- a/mteb/models/gritlm_models.py
+++ b/mteb/models/gritlm_models.py
@@ -17,7 +17,7 @@ def gritlm_instruction(instruction: str = "") -> str:
 
 
 gritlm7b = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         instruct_wrapper,
         model_name_or_path="GritLM/GritLM-7B",
         instruction_template=gritlm_instruction,
@@ -40,7 +40,7 @@ def gritlm_instruction(instruction: str = "") -> str:
     use_instructions=True,
 )
 gritlm8x7b = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         instruct_wrapper,
         model_name_or_path="GritLM/GritLM-8x7B",
         instruction_template=gritlm_instruction,
diff --git a/mteb/models/gte_models.py b/mteb/models/gte_models.py
index 2358ef6d5..82213b978 100644
--- a/mteb/models/gte_models.py
+++ b/mteb/models/gte_models.py
@@ -2,15 +2,21 @@
 
 from functools import partial
 
+import torch
+
 from mteb.model_meta import ModelMeta
+from mteb.models.instruct_wrapper import instruct_wrapper
+
+
+def instruction_template(instruction: str) -> str:
+    return f"Instruct: {instruction}\nQuery: " if instruction else ""
 
-from .instruct_wrapper import instruct_wrapper
 
 gte_Qwen2_7B_instruct = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         instruct_wrapper,
         model_name_or_path="Alibaba-NLP/gte-Qwen2-7B-instruct",
-        instruction_template="Instruct: {instruction}\nQuery: ",
+        instruction_template=instruction_template,
         attn="cccc",
         pooling_method="lasttoken",
         mode="embedding",
@@ -33,3 +39,59 @@
     framework=["Sentence Transformers", "PyTorch"],
     use_instructions=True,
 )
+
+
+gte_Qwen1_5_7B_instruct = ModelMeta(
+    loader=partial(  # type: ignore
+        instruct_wrapper,
+        model_name_or_path="Alibaba-NLP/gte-Qwen1.5-7B-instruct",
+        instruction_template=instruction_template,
+        attn="cccc",
+        pooling_method="lasttoken",
+        mode="embedding",
+        torch_dtype="auto",
+        normalized=True,
+    ),
+    name="Alibaba-NLP/gte-Qwen1.5-7B-instruct",
+    languages=["eng_Latn"],
+    open_weights=True,
+    revision="07d27e5226328010336563bc1b564a5e3436a298",
+    release_date="2024-04-20",  # initial commit of hf model.
+    n_parameters=7_720_000_000,
+    memory_usage=None,
+    embed_dim=4096,
+    license="apache-2.0",
+    max_tokens=32768,
+    reference="https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct",
+    similarity_fn_name="cosine",
+    framework=["Sentence Transformers", "PyTorch"],
+    use_instructions=True,
+)
+
+
+gte_Qwen2_1_5B_instruct = ModelMeta(
+    loader=partial(  # type: ignore
+        instruct_wrapper,
+        model_name_or_path="Alibaba-NLP/gte-Qwen2-1.5B-instruct",
+        instruction_template=instruction_template,
+        attn="cccc",
+        pooling_method="lasttoken",
+        mode="embedding",
+        torch_dtype="auto",
+        normalized=True,
+    ),
+    name="Alibaba-NLP/gte-Qwen2-1.5B-instruct",
+    languages=["eng_Latn"],
+    open_weights=True,
+    revision="c6c1b92f4a3e1b92b326ad29dd3c8433457df8dd",
+    release_date="2024-07-29",  # initial commit of hf model.
+    n_parameters=1_780_000_000,
+    memory_usage=None,
+    embed_dim=8960,
+    license="apache-2.0",
+    max_tokens=131072,
+    reference="https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct",
+    similarity_fn_name="cosine",
+    framework=["Sentence Transformers", "PyTorch"],
+    use_instructions=True,
+)
diff --git a/mteb/models/jina_models.py b/mteb/models/jina_models.py
index b103e174e..7705daec8 100644
--- a/mteb/models/jina_models.py
+++ b/mteb/models/jina_models.py
@@ -191,7 +191,7 @@ def encode(
 
 
 jina_embeddings_v3 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         JinaWrapper,
         model="jinaai/jina-embeddings-v3",
         revision="215a6e121fa0183376388ac6b1ae230326bfeaed",
diff --git a/mteb/models/linq_models.py b/mteb/models/linq_models.py
new file mode 100644
index 000000000..48e86ac8d
--- /dev/null
+++ b/mteb/models/linq_models.py
@@ -0,0 +1,40 @@
+from __future__ import annotations
+
+from functools import partial
+
+import torch
+
+from mteb.model_meta import ModelMeta
+from mteb.models.instruct_wrapper import instruct_wrapper
+
+
+def instruction_template(instruction: str) -> str:
+    return f"Instruct: {instruction}\nQuery: " if instruction else ""
+
+
+Linq_Embed_Mistral = ModelMeta(
+    loader=partial(  # type: ignore
+        instruct_wrapper,
+        model_name_or_path="Linq-AI-Research/Linq-Embed-Mistral",
+        instruction_template=instruction_template,
+        attn="cccc",
+        pooling_method="lasttoken",
+        mode="embedding",
+        torch_dtype=torch.bfloat16,
+        normalized=True,
+    ),
+    name="Linq-AI-Research/Linq-Embed-Mistral",
+    languages=["eng_Latn"],
+    open_weights=True,
+    revision="0c1a0b0589177079acc552433cad51d7c9132379",
+    release_date="2024-05-29",  # initial commit of hf model.
+    n_parameters=7_110_000_000,
+    memory_usage=None,
+    embed_dim=4096,
+    license="cc-by-nc-4.0",
+    max_tokens=32768,
+    reference="https://huggingface.co/Linq-AI-Research/Linq-Embed-Mistral",
+    similarity_fn_name="cosine",
+    framework=["Sentence Transformers", "PyTorch"],
+    use_instructions=True,
+)
diff --git a/mteb/models/mxbai_models.py b/mteb/models/mxbai_models.py
index ce7d1808b..5dfb9dc42 100644
--- a/mteb/models/mxbai_models.py
+++ b/mteb/models/mxbai_models.py
@@ -5,7 +5,7 @@
 from mteb.model_meta import ModelMeta, sentence_transformers_loader
 
 mxbai_embed_large_v1 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="mixedbread-ai/mxbai-embed-large-v1",
         revision="990580e27d329c7408b3741ecff85876e128e203",
diff --git a/mteb/models/nvidia_models.py b/mteb/models/nvidia_models.py
new file mode 100644
index 000000000..b3b11f559
--- /dev/null
+++ b/mteb/models/nvidia_models.py
@@ -0,0 +1,112 @@
+from __future__ import annotations
+
+import logging
+from collections.abc import Sequence
+from functools import partial
+from typing import Any
+
+import numpy as np
+import torch
+from sentence_transformers import CrossEncoder, SentenceTransformer
+
+from mteb.encoder_interface import PromptType
+from mteb.model_meta import ModelMeta
+from mteb.models.sentence_transformer_wrapper import SentenceTransformerWrapper
+
+logger = logging.getLogger(__name__)
+
+
+def instruction_template(instruction: str) -> str:
+    return f"Instruct: {instruction}\nQuery: " if instruction else ""
+
+
+class NvEmbedWrapper(SentenceTransformerWrapper):
+    def __init__(
+        self,
+        model: str | SentenceTransformer | CrossEncoder,
+        revision: str | None = None,
+        model_prompts: dict[str, str] | None = None,
+        **kwargs,
+    ) -> None:
+        super().__init__(model, revision, model_prompts, **kwargs)
+        self.model.max_seq_length = 32768
+        self.model.tokenizer.padding_side = "right"
+
+    def encode(
+        self,
+        sentences: Sequence[str],
+        *,
+        task_name: str,
+        prompt_type: PromptType | None = None,
+        **kwargs: Any,
+    ) -> np.ndarray:
+        # Add eos token to each input example
+        sentences = [example + self.model.tokenizer.eos_token for example in sentences]
+
+        instruction = ""
+        if prompt_type == PromptType.query:
+            instruction = self.get_instruction(task_name, prompt_type)
+
+        prompt = instruction_template(instruction)
+
+        if prompt:
+            logger.info(f"Using {prompt=} for task={task_name} {prompt_type=}")
+        else:
+            logger.info(f"No model prompts found for task={task_name} {prompt_type=}")
+
+        logger.info(f"Encoding {len(sentences)} sentences.")
+
+        embeddings = self.model.encode(
+            sentences,
+            prompt=prompt,
+            normalize_embeddings=True,
+            **kwargs,
+        )
+        if isinstance(embeddings, torch.Tensor):
+            embeddings = embeddings.cpu().detach().float().numpy()
+        return embeddings
+
+
+NV_embed_v2 = ModelMeta(
+    loader=partial(  # type: ignore
+        NvEmbedWrapper,
+        model="nvidia/NV-Embed-v2",
+        trust_remote_code=True,
+    ),
+    name="nvidia/NV-Embed-v2",
+    languages=["eng_Latn"],
+    open_weights=True,
+    revision="7604d305b621f14095a1aa23d351674c2859553a",
+    release_date="2024-09-09",  # initial commit of hf model.
+    n_parameters=7_850_000_000,
+    memory_usage=None,
+    embed_dim=4096,
+    license="cc-by-nc-4.0",
+    max_tokens=32768,
+    reference="https://huggingface.co/nvidia/NV-Embed-v2",
+    similarity_fn_name="cosine",
+    framework=["Sentence Transformers", "PyTorch"],
+    use_instructions=True,
+)
+
+NV_embed_v1 = ModelMeta(
+    loader=partial(  # type: ignore
+        NvEmbedWrapper,
+        model="nvidia/NV-Embed-v1",
+        trust_remote_code=True,
+    ),
+    name="nvidia/NV-Embed-v1",
+    languages=["eng_Latn"],
+    open_weights=True,
+    revision="570834afd5fef5bf3a3c2311a2b6e0a66f6f4f2c",
+    release_date="2024-09-13",  # initial commit of hf model.
+    n_parameters=7_850_000_000,
+    memory_usage=None,
+    embed_dim=4096,
+    license="cc-by-nc-4.0",
+    max_tokens=32768,
+    reference="https://huggingface.co/nvidia/NV-Embed-v1",
+    similarity_fn_name="cosine",
+    framework=["Sentence Transformers", "PyTorch"],
+    use_instructions=True,
+)
diff --git a/mteb/models/overview.py b/mteb/models/overview.py
index 1db236969..8d98b9a02 100644
--- a/mteb/models/overview.py
+++ b/mteb/models/overview.py
@@ -18,9 +18,11 @@
     gritlm_models,
     gte_models,
     jina_models,
+    linq_models,
     llm2vec_models,
     mxbai_models,
     nomic_models,
+    nvidia_models,
     openai_models,
     promptriever_models,
     repllama_models,
@@ -43,24 +45,26 @@
     e5_instruct,
     e5_models,
     google_models,
+    google_models,
     gritlm_models,
     gte_models,
+    jina_models,
+    linq_models,
     llm2vec_models,
     mxbai_models,
     nomic_models,
+    nvidia_models,
     openai_models,
+    promptriever_models,
+    repllama_models,
+    rerankers_custom,
+    rerankers_monot5_based,
     ru_sentence_models,
     salesforce_models,
     sentence_transformers_models,
-    voyage_models,
-    google_models,
-    repllama_models,
-    promptriever_models,
-    jina_models,
-    uae_models,
     stella_models,
-    rerankers_monot5_based,
-    rerankers_custom,
+    uae_models,
+    voyage_models,
 ]
 MODEL_REGISTRY = {}
 
diff --git a/mteb/models/rerankers_custom.py b/mteb/models/rerankers_custom.py
index dc354a550..40977f1e0 100644
--- a/mteb/models/rerankers_custom.py
+++ b/mteb/models/rerankers_custom.py
@@ -175,7 +175,7 @@ def loader_inner(**kwargs: Any) -> Encoder:
 
 
 monobert_large = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=MonoBERTReranker,
         model_name_or_path="castorini/monobert-large-msmarco",
@@ -190,7 +190,7 @@ def loader_inner(**kwargs: Any) -> Encoder:
 
 # languages unclear: https://huggingface.co/jinaai/jina-reranker-v2-base-multilingual/discussions/28
 jina_reranker_multilingual = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=JinaReranker,
         model_name_or_path="jinaai/jina-reranker-v2-base-multilingual",
@@ -204,7 +204,7 @@ def loader_inner(**kwargs: Any) -> Encoder:
 )
 
 bge_reranker_v2_m3 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=BGEReranker,
         model_name_or_path="BAAI/bge-reranker-v2-m3",
diff --git a/mteb/models/rerankers_monot5_based.py b/mteb/models/rerankers_monot5_based.py
index aef4a19e7..b96897ee5 100644
--- a/mteb/models/rerankers_monot5_based.py
+++ b/mteb/models/rerankers_monot5_based.py
@@ -276,7 +276,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 
 
 monot5_small = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=MonoT5Reranker,
         model_name_or_path="castorini/monot5-small-msmarco-10k",
@@ -290,7 +290,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 )
 
 monot5_base = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=MonoT5Reranker,
         model_name_or_path="castorini/monot5-base-msmarco-10k",
@@ -304,7 +304,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 )
 
 monot5_large = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=MonoT5Reranker,
         model_name_or_path="castorini/monot5-large-msmarco-10k",
@@ -318,7 +318,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 )
 
 monot5_3b = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=MonoT5Reranker,
         model_name_or_path="castorini/monot5-3b-msmarco-10k",
@@ -332,7 +332,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 )
 
 flant5_base = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=FLANT5Reranker,
         model_name_or_path="google/flan-t5-base",
@@ -346,7 +346,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 )
 
 flant5_large = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=FLANT5Reranker,
         model_name_or_path="google/flan-t5-large",
@@ -360,7 +360,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 )
 
 flant5_xl = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=FLANT5Reranker,
         model_name_or_path="google/flan-t5-xl",
@@ -374,7 +374,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 )
 
 flant5_xxl = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=FLANT5Reranker,
         model_name_or_path="google/flan-t5-xxl",
@@ -389,7 +389,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 
 
 llama2_7b = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=LlamaReranker,
         model_name_or_path="meta-llama/Llama-2-7b-hf",
@@ -403,7 +403,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 )
 
 llama2_7b_chat = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=LlamaReranker,
         model_name_or_path="meta-llama/Llama-2-7b-chat-hf",
@@ -417,7 +417,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 )
 
 mistral_7b = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=MistralReranker,
         model_name_or_path="mistralai/Mistral-7B-Instruct-v0.2",
@@ -431,7 +431,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 )
 
 followir_7b = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=FollowIRReranker,
         model_name_or_path="jhu-clsp/FollowIR-7B",
@@ -550,7 +550,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 ]
 
 mt5_base_mmarco_v2 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=MonoT5Reranker,
         model_name_or_path="unicamp-dl/mt5-base-mmarco-v2",
@@ -564,7 +564,7 @@ def get_prediction_tokens(self, *args, **kwargs):
 )
 
 mt5_13b_mmarco_100k = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         _loader,
         wrapper=MonoT5Reranker,
         model_name_or_path="unicamp-dl/mt5-13b-mmarco-100k",
diff --git a/mteb/models/ru_sentence_models.py b/mteb/models/ru_sentence_models.py
index cfe896516..301892e07 100644
--- a/mteb/models/ru_sentence_models.py
+++ b/mteb/models/ru_sentence_models.py
@@ -75,7 +75,7 @@
 )
 
 user_base_ru = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="deepvk/USER-base",
         revision="436a489a2087d61aa670b3496a9915f84e46c861",
@@ -218,7 +218,7 @@
 
 
 rosberta_ru_en = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         sentence_transformers_loader,
         model_name="ai-forever/ru-en-RoSBERTa",
         revision="89fb1651989adbb1cfcfdedafd7d102951ad0555",
diff --git a/mteb/models/salesforce_models.py b/mteb/models/salesforce_models.py
index eabc4352a..5ef104f23 100644
--- a/mteb/models/salesforce_models.py
+++ b/mteb/models/salesforce_models.py
@@ -5,23 +5,22 @@
 import torch
 
 from mteb.model_meta import ModelMeta
+from mteb.models.instruct_wrapper import instruct_wrapper
 
-from .instruct_wrapper import instruct_wrapper
 
-
-def sfr_instruction(instruction: str) -> str:
-    return f"Instruct: {instruction}\nQuery: "
+def instruction_template(instruction: str) -> str:
+    return f"Instruct: {instruction}\nQuery: " if instruction else ""
 
 
 SFR_Embedding_2_R = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         instruct_wrapper,
         model_name_or_path="Salesforce/SFR-Embedding-2_R",
-        instruction_template=sfr_instruction,
+        instruction_template=instruction_template,
         attn="cccc",
         pooling_method="lasttoken",
         mode="embedding",
-        torch_dtype=torch.bfloat16,
+        torch_dtype="auto",
         # The ST script does not normalize while the HF one does so unclear what to do
         # https://huggingface.co/Salesforce/SFR-Embedding-2_R
         normalized=True,
@@ -41,3 +40,31 @@ def sfr_instruction(instruction: str) -> str:
     framework=["Sentence Transformers", "PyTorch"],
     use_instructions=True,
 )
+
+
+SFR_Embedding_Mistral = ModelMeta(
+    loader=partial(  # type: ignore
+        instruct_wrapper,
+        model_name_or_path="Salesforce/SFR-Embedding-Mistral",
+        instruction_template=instruction_template,
+        attn="cccc",
+        pooling_method="lasttoken",
+        mode="embedding",
+        torch_dtype="auto",
+        normalized=True,
+    ),
+    name="Salesforce/SFR-Embedding-Mistral",
+    languages=["eng_Latn"],
+    open_weights=True,
+    revision="938c560d1c236aa563b2dbdf084f28ab28bccb11",
+    release_date="2024-01-24",  # initial commit of hf model.
+    n_parameters=7_110_000_000,
+    memory_usage=None,
+    embed_dim=4096,
+    license="cc-by-nc-4.0",
+    max_tokens=32768,
+    reference="https://huggingface.co/Salesforce/SFR-Embedding-Mistral",
+    similarity_fn_name="cosine",
+    framework=["Sentence Transformers", "PyTorch"],
+    use_instructions=True,
+)
diff --git a/mteb/models/stella_models.py b/mteb/models/stella_models.py
index 8fc19fd06..153ee6aa9 100644
--- a/mteb/models/stella_models.py
+++ b/mteb/models/stella_models.py
@@ -7,7 +7,7 @@
 
 stella_en_400M = ModelMeta(
     # https://huggingface.co/dunzhang/stella_en_400M_v5/discussions/21#671a6205ac1e2416090f2bf4
-    loader=partial(
+    loader=partial(  # type: ignore
         instruct_wrapper,
         model_name_or_path="dunzhang/stella_en_400M_v5",
         attn="cccc",
@@ -31,7 +31,7 @@
 )
 
 stella_en_1_5b = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         instruct_wrapper,
         model_name_or_path="dunzhang/stella_en_1.5B_v5",
         attn="cccc",
diff --git a/mteb/models/uae_models.py b/mteb/models/uae_models.py
index b18240b47..942d50894 100644
--- a/mteb/models/uae_models.py
+++ b/mteb/models/uae_models.py
@@ -52,7 +52,7 @@ def encode(
 
 
 uae_large_v1 = ModelMeta(
-    loader=partial(
+    loader=partial(  # type: ignore
         UAEWrapper,
         model="WhereIsAI/UAE-Large-V1",
         revision="369c368f70f16a613f19f5598d4f12d9f44235d4",
diff --git a/mteb/models/voyage_models.py b/mteb/models/voyage_models.py
index ea6b25bde..d63f132cf 100644
--- a/mteb/models/voyage_models.py
+++ b/mteb/models/voyage_models.py
@@ -145,7 +145,7 @@ def _batched_encode(
     revision="1",
     release_date="2024-05-05",
     languages=None,  # supported languages not specified
-    loader=partial(
+    loader=partial(  # type: ignore
         VoyageWrapper,
         model_name="voyage-large-2-instruct",
         model_prompts=model_prompts,
@@ -167,7 +167,7 @@ def _batched_encode(
     revision="1",
     release_date="2024-05-30",
     languages=None,  # supported languages not specified
-    loader=partial(
+    loader=partial(  # type: ignore
         VoyageWrapper,
         model_name="voyage-finance-2",
         model_prompts=model_prompts,
@@ -189,7 +189,7 @@ def _batched_encode(
     revision="1",
     release_date="2024-04-15",
     languages=None,  # supported languages not specified
-    loader=partial(
+    loader=partial(  # type: ignore
         VoyageWrapper,
         model_name="voyage-law-2",
         model_prompts=model_prompts,
@@ -211,7 +211,7 @@ def _batched_encode(
     revision="1",
     release_date="2024-01-23",
     languages=None,  # supported languages not specified
-    loader=partial(
+    loader=partial(  # type: ignore
         VoyageWrapper,
         model_name="voyage-code-2",
         model_prompts=model_prompts,
@@ -233,7 +233,7 @@ def _batched_encode(
     revision="1",
     release_date="2023-10-29",
     languages=None,  # supported languages not specified
-    loader=partial(
+    loader=partial(  # type: ignore
         VoyageWrapper,
         model_name="voyage-large-2",
         model_prompts=model_prompts,
@@ -255,7 +255,7 @@ def _batched_encode(
     revision="1",
     release_date="2023-10-29",
     languages=None,  # supported languages not specified
-    loader=partial(
+    loader=partial(  # type: ignore
         VoyageWrapper,
         model_name="voyage-2",
         model_prompts=model_prompts,
@@ -276,7 +276,7 @@ def _batched_encode(
     revision="1",
     release_date="2024-06-10",
     languages=None,  # supported languages not specified
-    loader=partial(
+    loader=partial(  # type: ignore
         VoyageWrapper,
         model_name="voyage-multilingual-2",
         model_prompts=model_prompts,