Integrate with Sentence Transformers (#6)

- Add Sentence Transformers compatibility (a24e3f030774c6b9f341acddc509ce1ff74a5ce4)

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+    "word_embedding_dimension": 2048,
+    "pooling_mode_cls_token": false,
+    "pooling_mode_mean_tokens": true,
+    "pooling_mode_max_tokens": false,
+    "pooling_mode_mean_sqrt_len_tokens": false,
+    "pooling_mode_weightedmean_tokens": false,
+    "pooling_mode_lasttoken": false,
+    "include_prompt": true
+}

README.md

@@ -8,9 +8,10 @@ tags:
   - text-embeddings
   - retrieval
   - semantic-search
+  - transformers
 language:
   - multilingual
-library_name: transformers
+library_name: sentence-transformers
 ---
 
 ## **Model Overview**
@@ -61,13 +62,46 @@ This NeMo embedding model is a transformer encoder - a fine-tuned version of Lla
 
 ### **Installation**
 
+### **Sentence Transformers Usage**
+
 The model requires transformers version 4.47.1.
 
+```bash
+pip install transformers==4.47.1 sentence-transformers
+```
+
+```python
+from sentence_transformers import SentenceTransformer
+
+model = SentenceTransformer("nvidia/llama-nemotron-embed-1b-v2", trust_remote_code=True)
+
+queries = [
+    "how much protein should a female eat",
+    "summit define",
+]
+documents = [
+    "As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.",
+    "Definition of summit for English Language Learners. : 1  the highest point of a mountain : the top of a mountain. : 2  the highest level. : 3  a meeting or series of meetings between the leaders of two or more governments."
+]
+
+query_embeddings = model.encode_query(queries, convert_to_tensor=True)
+document_embeddings = model.encode_document(documents, convert_to_tensor=True)
+
+# Compute similarity scores
+scores = model.similarity(query_embeddings, document_embeddings)
+"""
+tensor([[ 0.5968, -0.0454],
+        [-0.0336,  0.4613]], device='cuda:0')
+"""
+```
+
+### **Transformers Usage**
+You can also use transformers directly to run the model. The model requires transformers version 4.47.1.
+
 ```bash
 pip install transformers==4.47.1
 ```
 
-### **Usage**
 ```python
 import torch
 import torch.nn.functional as F
@@ -133,8 +167,6 @@ print(scores.tolist())
 
 #Similarity scores:
 #[[0.5968121290206909, -0.04534469544887543], [-0.03361201286315918, 0.46140915155410767]]
-
-
 ```
 
 #### vLLM Usage

config_sentence_transformers.json

@@ -0,0 +1,14 @@
+{
+  "model_type": "SentenceTransformer",
+  "__version__": {
+    "sentence_transformers": "5.0.1",
+    "transformers": "4.47.1",
+    "pytorch": "2.9.1+cu126"
+  },
+  "prompts": {
+    "query": "query: ",
+    "document": "passage: "
+  },
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+    "max_seq_length": 131072,
+    "do_lower_case": false
+}