enjalot commited on
Commit
f4125b8
1 Parent(s): 97922d9

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +46 -0
README.md CHANGED
@@ -32,4 +32,50 @@ configs:
32
  data_files:
33
  - split: train
34
  path: data/train-*
 
 
 
 
35
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
32
  data_files:
33
  - split: train
34
  path: data/train-*
35
+ license: apache-2.0
36
+ pretty_name: FineWeb-edu 10BT Sample embedded with nomic-text-v1.5
37
+ size_categories:
38
+ - 10M<n<100M
39
  ---
40
+ # FineWeb-edu 10BT Sample embedded with nomic-text-v1.5
41
+
42
+ The [FineWeb-edu 10BT sample](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu/tree/main/sample/10BT) was first chunked into 500 tokens (using bert-base-uncased) with 10% overlap resulting in 25 million rows and 10.5BT.
43
+ The chunks were then embedded using [nomic-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5).
44
+
45
+ ## Dataset Details
46
+
47
+ ### Dataset Description
48
+
49
+ - **Curated by:** Ian @enjalot Johnson
50
+ - **Funded by:** Latent Interfaces
51
+ - **License:** Apache license 2.0
52
+
53
+ ### Dataset Sources
54
+
55
+ - **Repository:** https://github.com/enjalot/fineweb-modal
56
+
57
+ ## Uses
58
+
59
+ ### Direct Use
60
+
61
+ The dataset was embedded with the `clustering: ` prefix, so the main usecase is clustering and feature extraction.
62
+ The motivation for making the dataset is to create training data for an [SAE to identify features](https://transformer-circuits.pub/2024/scaling-monosemanticity) in nomic-text-v1.5.
63
+
64
+ ## Dataset Structure
65
+
66
+ The columns of the dataset are:
67
+
68
+ - id: the document id in fineweb-edu
69
+ - url: the url of the document in fineweb-edu
70
+ - score: the score from fineweb-edu
71
+ - dump: the dump in fineweb-edu
72
+ - chunk_index: which chunk of the original document this is
73
+ - chunk_text: the text of the chunk
74
+ - chunk_tokens: the tokens tokenized by bert-base-uncased
75
+ - chunk_token_count: the number of tokens in this chunk
76
+ - embedding: the 768 dimension vector representing the nomic-text-v1.5 embedding
77
+ ## Dataset Creation
78
+
79
+ ### Curation Rationale
80
+ The 10BT Sample is big enough to warrant a scaled up process but manageable enough to be done on a small budget. Using on-demand CPUs and GPUs from modal.com the total cost was ~$60.
81
+