Update README.md

README.md

@@ -2634,11 +2634,12 @@ the model enables fast inference while delivering better performance than our sm
 It is recommended to use a single GPU for inference.
 Additionally, we provide the following options:
 
+- `jina-embedding-t-en-v1`: 14 million parameters.
 - `jina-embedding-s-en-v1`: 35 million parameters.
-- `jina-embedding-b-en-v1`: 110 million parameters  **(you are here)**.
+- `jina-embedding-b-en-v1`: 110 million parameters **(you are here)**.
 - `jina-embedding-l-en-v1`: 330 million parameters.
-- `jina-embedding-xl-en-v1`: 1.2 billion parameters (soon).
-- `jina-embedding-xxl-en-v1`: 6 billion parameters (soon).
+- `jina-embedding-1b-en-v1`: 1.2 billion parameters, 10* bert-base size (soon).
+- `jina-embedding-6b-en-v1`: 6 billion parameters 30* bert-base size(soon).
 
 ## Data & Parameters
 
@@ -2650,9 +2651,10 @@ We compared the model against `all-minilm-l6-v2`/`all-mpnet-base-v2` from sbert
 
 |Name|param    |dimension|
 |------------------------------|-----|------|
-|all-minilm-l6-v2|33m      |384|
+|all-minilm-l6-v2|23m      |384|
 |all-mpnet-base-v2 |110m     |768|
 |ada-embedding-002|Unknown/OpenAI API  |8192|
+|jina-embedding-t-en-v1|14m      |312|
 |jina-embedding-s-en-v1|35m      |512|
 |jina-embedding-b-en-v1|110m      |768|
 |jina-embedding-l-en-v1|330m      |1024|
@@ -2663,6 +2665,7 @@ We compared the model against `all-minilm-l6-v2`/`all-mpnet-base-v2` from sbert
 |all-minilm-l6-v2|0.724|0.806|0.756|0.854|0.79 |0.876|0.473   |0.876|0.645  |
 |all-mpnet-base-v2|0.726|0.835|**0.78** |0.857|0.8  |**0.906**|0.513   |0.875|0.656  |
 |ada-embedding-002|0.698|0.833|0.761|0.861|**0.86** |0.903|**0.685**   |0.876|**0.726**  |
+|jina-embedding-t-en-v1|0.714|0.775|0.723|0.825|0.771|0.863|0.479   |0.841|0.542  |
 |jina-embedding-s-en-v1|**0.743**|0.786|0.738|0.837|0.80|0.875|0.523   |0.857|0.524  |
 |jina-embedding-b-en-v1|0.735|0.792|0.752|0.851|0.801|0.89|0.546   |0.871|0.586  |
 |jina-embedding-l-en-v1|0.739|**0.844**|0.778|**0.863**|0.821|0.896|0.566   |**0.882**|0.608  |