Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10M - 100M
DOI:
spacemanidol
commited on
Commit
•
25673f8
1
Parent(s):
8756f5c
readme
Browse files
README.md
ADDED
@@ -0,0 +1,50 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
task_categories:
|
4 |
+
- question-answering
|
5 |
+
language:
|
6 |
+
- en
|
7 |
+
tags:
|
8 |
+
- TREC-RAG
|
9 |
+
- RAG
|
10 |
+
- MSMARCO
|
11 |
+
- MSMARCOV2.1
|
12 |
+
- Snowflake
|
13 |
+
- arctic
|
14 |
+
- arctic-embed
|
15 |
+
pretty_name: TREC-RAG-Embedding-Baseline
|
16 |
+
size_categories:
|
17 |
+
- 100M<n<1B
|
18 |
+
configs:
|
19 |
+
- config_name: corpus
|
20 |
+
data_files:
|
21 |
+
- split: train
|
22 |
+
path: corpus/*
|
23 |
+
---
|
24 |
+
|
25 |
+
# Snowflake Arctic Embed L Embeddings for MSMARCO V2.1 for TREC-RAG
|
26 |
+
|
27 |
+
This dataset contains the embeddings for the MSMARCO-V2.1 dataset which is used as the corpora for [TREC RAG](https://trec-rag.github.io/)
|
28 |
+
All embeddings are created using [Snowflake's Arctic Embed L](https://huggingface.co/Snowflake/snowflake-arctic-embed-l) and are intended to serve as a simple baseline for dense retrieval-based methods.
|
29 |
+
|
30 |
+
## Loading the dataset
|
31 |
+
|
32 |
+
### Loading the document embeddings
|
33 |
+
|
34 |
+
You can either load the dataset like this:
|
35 |
+
```python
|
36 |
+
from datasets import load_dataset
|
37 |
+
docs = load_dataset("Snowflake/msmarco-v2.1-snowflake-arctic-embed-l", split="train")
|
38 |
+
```
|
39 |
+
|
40 |
+
Or you can also stream it without downloading it before:
|
41 |
+
```python
|
42 |
+
from datasets import load_dataset
|
43 |
+
docs = load_dataset("Snowflake/msmarco-v2.1-snowflake-arctic-embed-l", split="train", streaming=True)
|
44 |
+
for doc in docs:
|
45 |
+
doc_id = doc['_id']
|
46 |
+
title = doc['title']
|
47 |
+
header = doc['header']
|
48 |
+
text = doc['text']
|
49 |
+
emb = doc['emb']
|
50 |
+
```
|