Update README.md

README.md

@@ -1,8 +1,45 @@
 ---
 pipeline_tag: sentence-similarity
+language: fr
+datasets:
+- stsb_multi_mt
 tags:
-- sentence-transformers
-- feature-extraction
-- sentence-similarity
-- transformers
+- Text
+- Sentence Similarity
+- Sentence-Embedding
+- camembert-base
+license: apache-2.0
+model-index:
+- name: sentence-flaubert-base by Van Tuan DANG
+  results:
+  - task: 
+      name: Sentence-Embedding
+      type: Text Similarity
+    dataset:
+      name: Text Similarity fr
+      type: stsb_multi_mt
+      args: fr
+    metrics:
+       - name: Test Pearson correlation coefficient
+         type: Pearson_correlation_coefficient
+         value:  xx.xx
+---
+## Pre-trained sentence embedding models are the state-of-the-art of Sentence Embeddings for French.
+Model is Fine-tuned using pre-trained [flaubert/flaubert_base_uncased](https://huggingface.co/flaubert/flaubert_base_uncased) and
+[Siamese BERT-Networks with 'sentences-transformers'](https://www.sbert.net/) combine with Augmented SBERT on dataset [stsb](https://huggingface.co/datasets/stsb_multi_mt/viewer/fr/train)
+
+
+## Usage
+The model can be used directly (without a language model) as follows:
 
+```python
+from sentence_transformers import SentenceTransformer
+model =  SentenceTransformer("Lajavaness/sentence-flaubert-base")
+sentences = ["Un avion est en train de décoller.",
+          "Un homme joue d'une grande flûte.",
+          "Un homme étale du fromage râpé sur une pizza.",
+          "Une personne jette un chat au plafond.",
+          "Une personne est en train de plier un morceau de papier.",
+          ]
+embeddings = model.encode(sentences)
+```