anastasiastasenko
commited on
Update README.md
Browse files
README.md
CHANGED
@@ -44,6 +44,19 @@ Pleias-3b-Preview was fully pretrained at Jean Zay on 192 h100s for about 20 day
|
|
44 |
|
45 |
Training schedule includes 518,000 steps (batch size 1,024) on a filtered and enhanced version of Common Corpus (1,086,324,736,000 tokens).
|
46 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
47 |
## Update
|
48 |
Pleias-3b-Preview is currently released as an early preview.
|
49 |
|
|
|
44 |
|
45 |
Training schedule includes 518,000 steps (batch size 1,024) on a filtered and enhanced version of Common Corpus (1,086,324,736,000 tokens).
|
46 |
|
47 |
+
Training Greenhouse Gas Emissions: Estimated total location-based greenhouse gas emissions were 16 tons CO2eq for training.
|
48 |
+
|
49 |
+
## Ethical Considerations
|
50 |
+
|
51 |
+
pleias-3B-Preview model, like all large language models, carries inherent ethical risks that require careful consideration. Our approach to mitigating these risks begins at the data level, where we exclusively use vetted sources, deliberately excluding CommonCrawl. The primary challenge comes from our public domain dataset component, which contains historical texts that may reflect outdated social norms and potentially harmful language, particularly regarding minoritized groups.
|
52 |
+
|
53 |
+
To address this, we implemented a systematic ethical filtering process using toxicity classifiers to identify extremely harmful content. We also employed synthetic rewriting techniques to transform mildly problematic passages while preserving the underlying informational value. This process significantly reduced potential societal harm without compromising the dataset's size or textual quality, resulting in notably low toxicity scores in benchmarks compared to other models.
|
54 |
+
|
55 |
+
Despite these preventive measures, users should be aware that the model has not undergone additional safety alignment procedures and may still produce problematic outputs. The model's capabilities in generative AI tasks must be balanced against the risks of bias, misinformation propagation, and autonomous decision-making challenges. We explicitly prohibit any malicious utilization and emphasize the responsibility of users to implement appropriate safeguards.
|
56 |
+
|
57 |
+
At Pleias, we continue to research and develop improved methods for creating safer and more equitable models and datasets. This includes ongoing work in toxicity reduction, bias mitigation, and the development of more sophisticated ethical filtering techniques.
|
58 |
+
|
59 |
+
|
60 |
## Update
|
61 |
Pleias-3b-Preview is currently released as an early preview.
|
62 |
|