# Cross-Encoder for MS Marco

This model is a generic masked language model fine tuned on stack overflow data.  It's base pre-trained model was the cross-encoder/ms-marco-MiniLM-L-12-v2 model.

The model can be used for creating vectors for search applications.  It was trained to be used in conjunction with a knn search with OpenSearch for a pet project I've been working on.  It's easiest to create document embeddings with the flair package as shown below.


## Usage with Transformers

```python
from flair.data import Sentence
from flair.embeddings import TransformerDocumentEmbeddings

sentence = Sentence("Text to be embedded.")
model = TransformerDocumentEmbeddings("model-name")
model.embed(sentence)
embeddings = sentence.embedding
```

{"license": "apache-2.0"}
transformers pytorch safetensors bert fill-mask license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #bert #fill-mask #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

# Cross-Encoder for MS Marco

This model is a generic masked language model fine tuned on stack overflow data.  It's base pre-trained model was the cross-encoder/ms-marco-MiniLM-L-12-v2 model.

The model can be used for creating vectors for search applications.  It was trained to be used in conjunction with a knn search with OpenSearch for a pet project I've been working on.  It's easiest to create document embeddings with the flair package as shown below.


## Usage with Transformers



# Cross-Encoder for MS Marco

This model is a generic masked language model fine tuned on stack overflow data.  It's base pre-trained model was the cross-encoder/ms-marco-MiniLM-L-12-v2 model.

The model can be used for creating vectors for search applications.  It was trained to be used in conjunction with a knn search with OpenSearch for a pet project I've been working on.  It's easiest to create document embeddings with the flair package as shown below. ## Usage with Transformers
TAGS
#transformers #pytorch #safetensors #bert #fill-mask #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # Cross-Encoder for MS Marco

This model is a generic masked language model fine tuned on stack overflow data.  It's base pre-trained model was the cross-encoder/ms-marco-MiniLM-L-12-v2 model.

The model can be used for creating vectors for search applications.  It was trained to be used in conjunction with a knn search with OpenSearch for a pet project I've been working on.  It's easiest to create document embeddings with the flair package as shown below. ## Usage with Transformers
passage: TAGS
#transformers #pytorch #safetensors #bert #fill-mask #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# Cross-Encoder for MS Marco

This model is a generic masked language model fine tuned on stack overflow data.  It's base pre-trained model was the cross-encoder/ms-marco-MiniLM-L-12-v2 model.

The model can be used for creating vectors for search applications.  It was trained to be used in conjunction with a knn search with OpenSearch for a pet project I've been working on.  It's easiest to create document embeddings with the flair package as shown below.## Usage with Transformers