Spaces:
Running
Running
Update README.md
Browse files
README.md
CHANGED
@@ -7,4 +7,46 @@ sdk: static
|
|
7 |
pinned: false
|
8 |
---
|
9 |
|
10 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
7 |
pinned: false
|
8 |
---
|
9 |
|
10 |
+
# 🔍 OverseerAI
|
11 |
+
|
12 |
+
## Mission
|
13 |
+
OverseerAI is dedicated to advancing open-source AI safety and content moderation tools. We develop state-of-the-art models and datasets for brand safety classification, making content moderation more accessible and efficient for developers and organizations.
|
14 |
+
|
15 |
+
## 🌟 Our Projects
|
16 |
+
|
17 |
+
### Datasets
|
18 |
+
#### [BrandSafe-16k](https://huggingface.co/datasets/OverseerAI/BrandSafe-16k)
|
19 |
+
A comprehensive dataset for training brand safety classification models, featuring 16 distinct risk categories:
|
20 |
+
- B1-PROFANITY: Explicit language and cursing
|
21 |
+
- B2-OFFENSIVE_SLANG: Informal offensive terms
|
22 |
+
- B3-COMPETITOR: Competitive brand mentions
|
23 |
+
- B4-BRAND_CRITICISM: Negative brand commentary
|
24 |
+
- B5-MISLEADING: Deceptive or false information
|
25 |
+
- B6-POLITICAL: Political content and discussions
|
26 |
+
- B7-RELIGIOUS: Religious themes and references
|
27 |
+
- B8-CONTROVERSIAL: Contentious topics
|
28 |
+
- B9-ADULT: Adult or mature content
|
29 |
+
- B10-VIOLENCE: Violent themes or descriptions
|
30 |
+
- B11-SUBSTANCE: Drug and alcohol references
|
31 |
+
- B12-HATE: Hate speech and discrimination
|
32 |
+
- B13-STEREOTYPE: Stereotypical content
|
33 |
+
- B14-BIAS: Biased viewpoints
|
34 |
+
- B15-UNPROFESSIONAL: Unprofessional content
|
35 |
+
- B16-MANIPULATION: Manipulative content
|
36 |
+
|
37 |
+
### Models
|
38 |
+
|
39 |
+
#### [vision-1](https://huggingface.co/OverseerAI/vision-1)
|
40 |
+
Our flagship model for brand safety classification:
|
41 |
+
- Architecture: Meta Llama 3.1 (15GB)
|
42 |
+
- Full precision model optimized for high accuracy
|
43 |
+
- Trained on BrandSafe-16k dataset
|
44 |
+
- Ideal for production deployments with high-end GPU resources
|
45 |
+
|
46 |
+
#### [vision-1-mini](https://huggingface.co/OverseerAI/vision-1-mini)
|
47 |
+
A lightweight, optimized version of vision-1:
|
48 |
+
- Size: 4.58 GiB
|
49 |
+
- Architecture: Llama 3.1 8B
|
50 |
+
- Quantization: GGUF V3 (Q4_K)
|
51 |
+
- Optimized for Apple Silicon
|
52 |
+
- Fast load time:
|