Update README.md

README.md

@@ -5628,22 +5628,23 @@ print(scores.tolist())
 
 You can use the [scripts/eval_mteb.py](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct/blob/main/scripts/eval_mteb.py) to reproduce the following result of **gte-Qwen2-7B-instruct** on MTEB(English)/C-MTEB(Chinese):
 
-| Model Name | MTEB(56)  | C-MTEB(35) | 
-|:----:|:---------:|:----------:| 
-| [bge-base-en-1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) |   64.23   |     -      | 
-| [bge-large-en-1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) |   63.55   |     -      |
-| [gte-large-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) |   65.39   |     -      |
-| [gte-base-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) |   64.11   |     -      |
-| [mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) |   64.68   |     -      |
-| [acge_text_embedding](https://huggingface.co/aspire/acge_text_embedding) |     -     |   69.07    | 
-| [stella-mrl-large-zh-v3.5-1792d](https://huggingface.co/infgrad/stella-mrl-large-zh-v3.5-1792d) |     -     |   68.55    |
-| [gte-large-zh](https://huggingface.co/thenlper/gte-large-zh) |     -     |   66.72    |
-| [multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) |   59.45   |   56.21    | 
-| [multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) |   61.50   |   58.81    | 
-| [e5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) |   66.63   |   60.81    | 
-| [gte-Qwen1.5-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) |   67.34   |   69.52    |
-| [NV-Embed-v1](https://huggingface.co/nvidia/NV-Embed-v1) |   69.32   |     -      |
-| [**gte-Qwen2-7B-instruct**](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct) | **70.24** | **72.05**  |
+| Model Name | MTEB(56)  | C-MTEB(35) | MTEB-fr(26) | MTEB-pl(26) | 
+|:----:|:---------:|:----------:|:----------:|:----------:|
+| [bge-base-en-1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) |   64.23   |     -      |  - | - |
+| [bge-large-en-1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) |   63.55   |     -      | - | - |
+| [gte-large-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) |   65.39   |     -      |  - | - |
+| [gte-base-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) |   64.11   |     -      |  - | - |
+| [mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) |   64.68   |     -      |  - | - |
+| [acge_text_embedding](https://huggingface.co/aspire/acge_text_embedding) |     -     |   69.07    |   - | - |
+| [stella-mrl-large-zh-v3.5-1792d](https://huggingface.co/infgrad/stella-mrl-large-zh-v3.5-1792d) |     -     |   68.55    |  - | - |
+| [gte-large-zh](https://huggingface.co/thenlper/gte-large-zh) |     -     |   66.72    |  - | - |
+| [multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) |   59.45   |   56.21    |   - | - |
+| [multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) |   61.50   |   58.81    |   - | - |
+| [e5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) |   66.63   |   60.81    |   - | - |
+| [gte-Qwen1.5-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) |   67.34   |   69.52    |  - | - |
+| [NV-Embed-v1](https://huggingface.co/nvidia/NV-Embed-v1) |   69.32   |     -      |  - | - |
+| [**gte-Qwen2-7B-instruct**](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct) | **70.24** | **72.05**  | **68.25**   | **67.86** |
+| gte-Qwen2-1.5B-instruc(https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct) | 67.16 | 67.65  | 66.60 | 64.04 |
 
 ### GTE Models
 
@@ -5661,6 +5662,7 @@ The gte series models have consistently released two types of models: encoder-on
 |        [GTE-base-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-base-en-v1.5)        | English | 8192 |    768    |             0.51GB              |
 | [GTE-Qwen1.5-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) | Multilingual | 32000 | 4096 | 26.45GB |
 |   [GTE-Qwen2-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct)   | Multilingual | 32000 | 3584 | 26.45GB |
+|   [GTE-Qwen2-1.5B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct)   | Multilingual | 32000 | 1536 | 6.62GB |
 
 ## Citation