asmud commited on
Commit
57e0da1
·
verified ·
1 Parent(s): ab0abd6

Upload folder using huggingface_hub

Browse files
Files changed (3) hide show
  1. README.md +23 -1
  2. SETUP.md +1 -1
  3. USAGE_EXAMPLES.md +1 -1
README.md CHANGED
@@ -125,6 +125,26 @@ model-index:
125
 
126
  This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [nomic-ai/nomic-embed-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5) specifically for **Indonesian language** text embedding tasks. It maps Indonesian sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
127
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
128
  ## 🇮🇩 **Specialized for Indonesian Language**
129
 
130
  This model is optimized for Indonesian text understanding across multiple domains including:
@@ -175,12 +195,14 @@ First install the Sentence Transformers library:
175
  pip install -U sentence-transformers
176
  ```
177
 
 
 
178
  Then you can load this model and run inference.
179
  ```python
180
  from sentence_transformers import SentenceTransformer
181
 
182
  # Download from the 🤗 Hub
183
- model = SentenceTransformer("asmud/nomic-embed-indonesian")
184
  # Run inference with Indonesian text
185
  sentences = [
186
  'search_query: Apa itu kecerdasan buatan?',
 
125
 
126
  This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [nomic-ai/nomic-embed-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5) specifically for **Indonesian language** text embedding tasks. It maps Indonesian sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
127
 
128
+ ## 🚀 Quick Start
129
+
130
+ ```python
131
+ from sentence_transformers import SentenceTransformer
132
+
133
+ # Load the model (requires trust_remote_code=True)
134
+ model = SentenceTransformer("asmud/nomic-embed-indonesian", trust_remote_code=True)
135
+
136
+ # Indonesian text examples
137
+ texts = [
138
+ "search_query: Apa itu kecerdasan buatan?",
139
+ "search_document: Kecerdasan buatan adalah teknologi yang memungkinkan mesin belajar",
140
+ "classification: Produk ini sangat berkualitas (sentimen: positif)"
141
+ ]
142
+
143
+ # Generate embeddings
144
+ embeddings = model.encode(texts)
145
+ print(f"Embedding shape: {embeddings.shape}") # (3, 768)
146
+ ```
147
+
148
  ## 🇮🇩 **Specialized for Indonesian Language**
149
 
150
  This model is optimized for Indonesian text understanding across multiple domains including:
 
195
  pip install -U sentence-transformers
196
  ```
197
 
198
+ ⚠️ **Important**: This model requires `trust_remote_code=True` due to custom model architecture.
199
+
200
  Then you can load this model and run inference.
201
  ```python
202
  from sentence_transformers import SentenceTransformer
203
 
204
  # Download from the 🤗 Hub
205
+ model = SentenceTransformer("asmud/nomic-embed-indonesian", trust_remote_code=True)
206
  # Run inference with Indonesian text
207
  sentences = [
208
  'search_query: Apa itu kecerdasan buatan?',
SETUP.md CHANGED
@@ -74,7 +74,7 @@ After uploading, verify the model works:
74
  from sentence_transformers import SentenceTransformer
75
 
76
  # Load the uploaded model
77
- model = SentenceTransformer("asmud/nomic-embed-indonesian")
78
 
79
  # Test Indonesian text
80
  texts = [
 
74
  from sentence_transformers import SentenceTransformer
75
 
76
  # Load the uploaded model
77
+ model = SentenceTransformer("asmud/nomic-embed-indonesian", trust_remote_code=True)
78
 
79
  # Test Indonesian text
80
  texts = [
USAGE_EXAMPLES.md CHANGED
@@ -7,7 +7,7 @@ from sentence_transformers import SentenceTransformer
7
  from sklearn.metrics.pairwise import cosine_similarity
8
  import numpy as np
9
 
10
- model = SentenceTransformer("asmud/nomic-embed-indonesian")
11
 
12
  # Indonesian search example
13
  query = "search_query: Bagaimana cara memasak rendang?"
 
7
  from sklearn.metrics.pairwise import cosine_similarity
8
  import numpy as np
9
 
10
+ model = SentenceTransformer("asmud/nomic-embed-indonesian", trust_remote_code=True)
11
 
12
  # Indonesian search example
13
  query = "search_query: Bagaimana cara memasak rendang?"