Add support for dangvantuan/sentence-camembert-base

docs/examples/Supported_Models.ipynb

@@ -178,6 +178,13 @@
        "      <td>Multilingual model, e5-large. Recommend using ...</td>\n",
        "      <td>2.240</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>dangvantuan/sentence-camembert-base</td>\n",
+       "      <td>768</td>\n",
+       "      <td>French embedding model</td>\n",
+       "      <td>0.440</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
@@ -200,6 +207,7 @@
        "13                             BAAI/bge-large-en-v1.5  1024   \n",
        "14                                 thenlper/gte-large  1024   \n",
        "15                     intfloat/multilingual-e5-large  1024   \n",
+       "16                dangvantuan/sentence-camembert-base  768    \n",
        "\n",
        "                                          description  size_in_GB  \n",
        "0                      Fast and Default English model       0.067  \n",
@@ -217,7 +225,8 @@
        "12  Sentence-transformers model for tasks like clu...       1.000  \n",
        "13                          Large English model, v1.5       1.200  \n",
        "14                Large general text embeddings model       1.200  \n",
-       "15  Multilingual model, e5-large. Recommend using ...       2.240  "
+       "15  Multilingual model, e5-large. Recommend using ...       2.240  \n",
+       "16 French embedding model                                   0.440  "
       ]
      },
      "execution_count": 6,

fastembed/text/e5_onnx_embedding.py

@@ -25,6 +25,16 @@
             "hf": "xenova/paraphrase-multilingual-mpnet-base-v2",
         },
     },
+    {
+        "model": "dangvantuan/sentence-camembert-base",
+        "dim": 768,
+        "description": "French embedding model",
+        "size_in_GB": 0.440,
+        "sources": {
+            "hf": "yashvardhan7/sentence-camembert-base_onnx",
+        },
+    },
+
 ]
 
 

tests/test_text_onnx_embeddings.py

@@ -28,6 +28,7 @@
     ),
     "thenlper/gte-large": np.array([-0.01920587, 0.00113156, -0.00708992, -0.00632304, -0.04025577]),
     "mixedbread-ai/mxbai-embed-large-v1": np.array([0.02295546, 0.03196154, 0.016512, -0.04031524, -0.0219634]),
+    "dangvantuan/sentence-camembert-base": np.array([-0.00152421, 0.07088307, -0.03992718, 0.00225199, 0.00442147]),
 }