Token Classification
Transformers
Safetensors
French
roberta
Inference Endpoints
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@@ -51,42 +51,42 @@ For space reasons, we show only the F1 of the different models. You can see the
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  </thead>
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  <tbody>
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  <tr>
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- <td rowspan="1"><br><a href="https://hf.co/Jean-Baptiste/camembert-ner">Jean-Baptiste/camembert-ner (110M)</a></td>
55
  <td><br>0.971</td>
56
  <td><br>0.947</td>
57
  <td><br>0.902</td>
58
  <td><br>0.663</td>
59
  </tr>
60
  <tr>
61
- <td rowspan="1"><br><a href="https://hf.co/cmarkea/distilcamembert-base-ner">cmarkea/distilcamembert-base-ner (67.5M)</a></td>
62
  <td><br>0.974</td>
63
  <td><br>0.948</td>
64
  <td><br>0.892</td>
65
  <td><br>0.658</td>
66
  </tr>
67
  <tr>
68
- <td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities</a></td>
69
  <td><br>0.978</td>
70
  <td><br>0.958</td>
71
  <td><br>0.903</td>
72
  <td><br>0.814</td>
73
  </tr>
74
  <tr>
75
- <td rowspan="1"><br>NERmembert2-4entities (this model) (111M)</td>
76
  <td><br>0.978</td>
77
  <td><br>0.958</td>
78
  <td><br>0.901</td>
79
  <td><br>0.806</td>
80
  </tr>
81
  <tr>
82
- <td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmemberta-4entities">NERmemberta-4entities (111M)</a></td>
83
  <td><br>0.979</td>
84
  <td><br>0.961</td>
85
  <td><br>0.915</td>
86
  <td><br>0.812</td>
87
  </tr>
88
  <tr>
89
- <td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmembert-large-4entities">NERmembert-large-4entities (336M)</a></td>
90
  <td><br><b>0.982</b></td>
91
  <td><br><b>0.964</b></td>
92
  <td><br><b>0.919</b></td>
@@ -169,7 +169,7 @@ For space reasons, we show only the F1 of the different models. You can see the
169
  <td><br>0.976</td>
170
  </tr>
171
  <tr>
172
- <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities</a></td>
173
  <td><br>Precision</td>
174
  <td><br>0.973</td>
175
  <td><br>0.951</td>
@@ -197,7 +197,7 @@ For space reasons, we show only the F1 of the different models. You can see the
197
  <td><br>0.984</td>
198
  </tr>
199
  <tr>
200
- <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert2-4entities">NERmembert2-4entities (this model) (111M)</a></td>
201
  <td><br>Precision</td>
202
  <td><br>0.973</td>
203
  <td><br>0.951</td>
@@ -316,14 +316,14 @@ For space reasons, we show only the F1 of the different models. You can see the
316
  <td><br>0.530</td>
317
  </tr>
318
  <tr>
319
- <td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities</a></td>
320
  <td><br>0.960</td>
321
  <td><br>0.890</td>
322
  <td><br>0.867</td>
323
  <td><br>0.852</td>
324
  </tr>
325
  <tr>
326
- <td rowspan="1"><br>NERmembert2-4entities (this model) (111M)</td>
327
  <td><br>0.964</td>
328
  <td><br>0.888</td>
329
  <td><br>0.864</td>
@@ -419,7 +419,7 @@ For space reasons, we show only the F1 of the different models. You can see the
419
  <td><br>0.881</td>
420
  </tr>
421
  <tr>
422
- <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities</a></td>
423
  <td><br>Precision</td>
424
  <td><br>0.954</td>
425
  <td><br>0.893</td>
@@ -447,7 +447,7 @@ For space reasons, we show only the F1 of the different models. You can see the
447
  <td><br>0.954</td>
448
  </tr>
449
  <tr>
450
- <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert2-4entities">NERmembert2-4entities (this model) (111M)</a></td>
451
  <td><br>Precision</td>
452
  <td><br>0.953</td>
453
  <td><br>0.890</td>
@@ -565,14 +565,14 @@ For space reasons, we show only the F1 of the different models. You can see the
565
  <td><br>0.430</td>
566
  </tr>
567
  <tr>
568
- <td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities</a></td>
569
  <td><br>0.985</td>
570
  <td><br>0.973</td>
571
  <td><br>0.938</td>
572
  <td><br>0.770</td>
573
  </tr>
574
  <tr>
575
- <td rowspan="1"><br>NERmembert2-4entities (this model) (111M)</td>
576
  <td><br>0.986</td>
577
  <td><br>0.974</td>
578
  <td><br>0.937</td>
@@ -668,7 +668,7 @@ For space reasons, we show only the F1 of the different models. You can see the
668
  <td><br>0.967</td>
669
  </tr>
670
  <tr>
671
- <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities</a></td>
672
  <td><br>Precision</td>
673
  <td><br>0.976</td>
674
  <td><br>0.961</td>
@@ -696,7 +696,7 @@ For space reasons, we show only the F1 of the different models. You can see the
696
  <td><br>0.983</td>
697
  </tr>
698
  <tr>
699
- <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert2-4entities">NERmembert2-4entities (this model) (111M)</a></td>
700
  <td><br>Precision</td>
701
  <td><br>0.976</td>
702
  <td><br>0.962</td>
@@ -813,14 +813,14 @@ For space reasons, we show only the F1 of the different models. You can see the
813
  <td><br>0.926</td>
814
  </tr>
815
  <tr>
816
- <td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities</a></td>
817
  <td><br>0.970</td>
818
  <td><br>0.945</td>
819
  <td><br>0.876</td>
820
  <td><br>0.872</td>
821
  </tr>
822
  <tr>
823
- <td rowspan="1"><br>NERmembert2-4entities (this model) (111M)</td>
824
  <td><br>0.968</td>
825
  <td><br>0.945</td>
826
  <td><br>0.874</td>
@@ -916,7 +916,7 @@ For space reasons, we show only the F1 of the different models. You can see the
916
  <td><br>0.991</td>
917
  </tr>
918
  <tr>
919
- <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities</a></td>
920
  <td><br>Precision</td>
921
  <td><br>0.970</td>
922
  <td><br>0.944</td>
@@ -944,7 +944,7 @@ For space reasons, we show only the F1 of the different models. You can see the
944
  <td><br>0.986</td>
945
  </tr>
946
  <tr>
947
- <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert2-4entities">NERmembert2-4entities (this model) (111M)</a></td>
948
  <td><br>Precision</td>
949
  <td><br>0.970</td>
950
  <td><br>0.942</td>
 
51
  </thead>
52
  <tbody>
53
  <tr>
54
+ <td rowspan="1"><br><a href="https://hf.co/Jean-Baptiste/camembert-ner">Jean-Baptiste/camembert-ner (110M, 512 tokens))</a></td>
55
  <td><br>0.971</td>
56
  <td><br>0.947</td>
57
  <td><br>0.902</td>
58
  <td><br>0.663</td>
59
  </tr>
60
  <tr>
61
+ <td rowspan="1"><br><a href="https://hf.co/cmarkea/distilcamembert-base-ner">cmarkea/distilcamembert-base-ner (67.5M, 512 tokens))</a></td>
62
  <td><br>0.974</td>
63
  <td><br>0.948</td>
64
  <td><br>0.892</td>
65
  <td><br>0.658</td>
66
  </tr>
67
  <tr>
68
+ <td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities (110M, 512 tokens)</a></td>
69
  <td><br>0.978</td>
70
  <td><br>0.958</td>
71
  <td><br>0.903</td>
72
  <td><br>0.814</td>
73
  </tr>
74
  <tr>
75
+ <td rowspan="1"><br>NERmembert2-4entities (this model) (111M, 512 tokens))</td>
76
  <td><br>0.978</td>
77
  <td><br>0.958</td>
78
  <td><br>0.901</td>
79
  <td><br>0.806</td>
80
  </tr>
81
  <tr>
82
+ <td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmemberta-4entities">NERmemberta-4entities (111M, 512 tokens))</a></td>
83
  <td><br>0.979</td>
84
  <td><br>0.961</td>
85
  <td><br>0.915</td>
86
  <td><br>0.812</td>
87
  </tr>
88
  <tr>
89
+ <td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmembert-large-4entities">NERmembert-large-4entities (336M, 512 tokens))</a></td>
90
  <td><br><b>0.982</b></td>
91
  <td><br><b>0.964</b></td>
92
  <td><br><b>0.919</b></td>
 
169
  <td><br>0.976</td>
170
  </tr>
171
  <tr>
172
+ <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities (110M)</a></td>
173
  <td><br>Precision</td>
174
  <td><br>0.973</td>
175
  <td><br>0.951</td>
 
197
  <td><br>0.984</td>
198
  </tr>
199
  <tr>
200
+ <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert2-4entities">NERmembert2-4entities (111M) (this model)</a></td>
201
  <td><br>Precision</td>
202
  <td><br>0.973</td>
203
  <td><br>0.951</td>
 
316
  <td><br>0.530</td>
317
  </tr>
318
  <tr>
319
+ <td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities (110M)</a></td>
320
  <td><br>0.960</td>
321
  <td><br>0.890</td>
322
  <td><br>0.867</td>
323
  <td><br>0.852</td>
324
  </tr>
325
  <tr>
326
+ <td rowspan="1"><br>NERmembert2-4entities (111M) (this model)</td>
327
  <td><br>0.964</td>
328
  <td><br>0.888</td>
329
  <td><br>0.864</td>
 
419
  <td><br>0.881</td>
420
  </tr>
421
  <tr>
422
+ <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities (110M)</a></td>
423
  <td><br>Precision</td>
424
  <td><br>0.954</td>
425
  <td><br>0.893</td>
 
447
  <td><br>0.954</td>
448
  </tr>
449
  <tr>
450
+ <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert2-4entities">NERmembert2-4entities (111M) (this model)</a></td>
451
  <td><br>Precision</td>
452
  <td><br>0.953</td>
453
  <td><br>0.890</td>
 
565
  <td><br>0.430</td>
566
  </tr>
567
  <tr>
568
+ <td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities (110M)</a></td>
569
  <td><br>0.985</td>
570
  <td><br>0.973</td>
571
  <td><br>0.938</td>
572
  <td><br>0.770</td>
573
  </tr>
574
  <tr>
575
+ <td rowspan="1"><br>NERmembert2-4entities (111M) (this model)</td>
576
  <td><br>0.986</td>
577
  <td><br>0.974</td>
578
  <td><br>0.937</td>
 
668
  <td><br>0.967</td>
669
  </tr>
670
  <tr>
671
+ <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities (110M)</a></td>
672
  <td><br>Precision</td>
673
  <td><br>0.976</td>
674
  <td><br>0.961</td>
 
696
  <td><br>0.983</td>
697
  </tr>
698
  <tr>
699
+ <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert2-4entities">NERmembert2-4entities (111M) (this model)</a></td>
700
  <td><br>Precision</td>
701
  <td><br>0.976</td>
702
  <td><br>0.962</td>
 
813
  <td><br>0.926</td>
814
  </tr>
815
  <tr>
816
+ <td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities (110M)</a></td>
817
  <td><br>0.970</td>
818
  <td><br>0.945</td>
819
  <td><br>0.876</td>
820
  <td><br>0.872</td>
821
  </tr>
822
  <tr>
823
+ <td rowspan="1"><br>NERmembert2-4entities (111M) (this model)</td>
824
  <td><br>0.968</td>
825
  <td><br>0.945</td>
826
  <td><br>0.874</td>
 
916
  <td><br>0.991</td>
917
  </tr>
918
  <tr>
919
+ <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities (110M)</a></td>
920
  <td><br>Precision</td>
921
  <td><br>0.970</td>
922
  <td><br>0.944</td>
 
944
  <td><br>0.986</td>
945
  </tr>
946
  <tr>
947
+ <td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert2-4entities">NERmembert2-4entities (111M) (this model)</a></td>
948
  <td><br>Precision</td>
949
  <td><br>0.970</td>
950
  <td><br>0.942</td>