Instructions to use facebook/dragon-roberta-query-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/dragon-roberta-query-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/dragon-roberta-query-encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("facebook/dragon-roberta-query-encoder") model = AutoModelForMaskedLM.from_pretrained("facebook/dragon-roberta-query-encoder") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -4,11 +4,18 @@ tags:
|
|
| 4 |
pipeline_tag: feature-extraction
|
| 5 |
---
|
| 6 |
DRAGON-RoBERTa is a BERT-base sized dense retriever initialized from [RoBERTa](https://huggingface.co/roberta-base) and further trained on the data augmented from MS MARCO corpus, following the approach described in [How to Train Your DRAGON:
|
| 7 |
-
Diverse Augmentation Towards Generalizable Dense Retrieval](
|
| 8 |
-
|
| 9 |
-
|
| 10 |
-
|
| 11 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 12 |
|
| 13 |
## Usage (HuggingFace Transformers)
|
| 14 |
Using the model directly available in HuggingFace transformers .
|
|
|
|
| 4 |
pipeline_tag: feature-extraction
|
| 5 |
---
|
| 6 |
DRAGON-RoBERTa is a BERT-base sized dense retriever initialized from [RoBERTa](https://huggingface.co/roberta-base) and further trained on the data augmented from MS MARCO corpus, following the approach described in [How to Train Your DRAGON:
|
| 7 |
+
Diverse Augmentation Towards Generalizable Dense Retrieval](https://arxiv.org/abs/2302.07452).
|
| 8 |
+
|
| 9 |
+
<p align="center">
|
| 10 |
+
<img src="https://raw.githubusercontent.com/facebookresearch/dpr-scale/main/dragon/images/teaser.png" width="600">
|
| 11 |
+
</p>
|
| 12 |
+
|
| 13 |
+
The associated GitHub repository is available here https://github.com/facebookresearch/dpr-scale/tree/main/dragon. We use asymmetric dual encoder, with two distinctly parameterized encoders. The following models are also available:
|
| 14 |
+
|
| 15 |
+
Model | Initialization | MARCO Dev | BEIR | Query Encoder Path | Context Encoder Path
|
| 16 |
+
|---|---|---|---|---|---
|
| 17 |
+
DRAGON+ | Shitao/RetroMAE| 39.0 | 47.4 | [facebook/dragon-plus-query-encoder](https://huggingface.co/facebook/dragon-plus-query-encoder) | [facebook/dragon-plus-context-encoder](https://huggingface.co/facebook/dragon-plus-context-encoder)
|
| 18 |
+
DRAGON-RoBERTa | RoBERTa-base | 39.4 | 47.2 | [facebook/dragon-roberta-query-encoder](https://huggingface.co/facebook/dragon-roberta-query-encoder) | [facebook/dragon-roberta-context-encoder](https://huggingface.co/facebook/dragon-roberta-context-encoder)
|
| 19 |
|
| 20 |
## Usage (HuggingFace Transformers)
|
| 21 |
Using the model directly available in HuggingFace transformers .
|