Update README.md

README.md

@@ -1,56 +1,55 @@
-
----
-library_name: sentence-transformers
-tags:
-- sentence-transformers
-- sentence-similarity
-- feature-extraction
-- autotrain
-base_model: BAAI/bge-m3
-widget:
-- source_sentence: 'search_query: i love autotrain'
-  sentences:
-  - 'search_query: huggingface auto train'
-  - 'search_query: hugging face auto train'
-  - 'search_query: i love autotrain'
-pipeline_tag: sentence-similarity
-datasets:
-- MR-Eder/embedding-triples
----
-
-# Model Trained Using AutoTrain
-
-- Problem type: Sentence Transformers
-
-## Validation Metrics
-No validation metrics available
-
-## Usage
-
-### Direct Usage (Sentence Transformers)
-
-First install the Sentence Transformers library:
-
-```bash
-pip install -U sentence-transformers
-```
-
-Then you can load this model and run inference.
-```python
-from sentence_transformers import SentenceTransformer
-
-# Download from the Hugging Face Hub
-model = SentenceTransformer("sentence_transformers_model_id")
-# Run inference
-sentences = [
-    'search_query: autotrain',
-    'search_query: auto train',
-    'search_query: i love autotrain',
-]
-embeddings = model.encode(sentences)
-print(embeddings.shape)
-
-# Get the similarity scores for the embeddings
-similarities = model.similarity(embeddings, embeddings)
-print(similarities.shape)
-```
+---
+library_name: sentence-transformers
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- autotrain
+base_model: BAAI/bge-m3
+widget:
+- source_sentence: 'search_query: i love autotrain'
+  sentences:
+  - 'search_query: huggingface auto train'
+  - 'search_query: hugging face auto train'
+  - 'search_query: i love autotrain'
+pipeline_tag: sentence-similarity
+datasets:
+- avemio-digital/GRAG-Embedding-Triples-Hessian-AI
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Sentence Transformers
+
+## Validation Metrics
+No validation metrics available
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the Hugging Face Hub
+model = SentenceTransformer("sentence_transformers_model_id")
+# Run inference
+sentences = [
+    'search_query: autotrain',
+    'search_query: auto train',
+    'search_query: i love autotrain',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities.shape)
+```