databricks
/

dolly-v2-3b

@@ -10,7 +10,7 @@ datasets:
 # dolly-v2-3b Model Card
 ## Summary
-Databricks’ `dolly-v2-3b`, an instruction-following large language model trained on the Databricks machine learning platform
 that is licensed for commercial use. Based on `pythia-2.8b`, Dolly is trained on ~15k instruction/response fine tuning records
 [`databricks-dolly-15k`](https://github.com/databrickslabs/dolly/tree/master/data) generated
 by Databricks employees in capability domains from the InstructGPT paper, including brainstorming, classification, closed QA, generation,
@@ -29,7 +29,7 @@ running inference for various GPU configurations.
 ## Model Overview
 `dolly-v2-3b` is a 2.8 billion parameter causal language model created by [Databricks](https://databricks.com/) that is derived from
-[EleutherAI’s](https://www.eleuther.ai/) [Pythia-2.8b](https://huggingface.co/EleutherAI/pythia-2.8b) and fine-tuned
 on a [~15K record instruction corpus](https://github.com/databrickslabs/dolly/tree/master/data) generated by Databricks employees and released under a permissive license (CC-BY-SA)
 ## Usage
@@ -139,7 +139,7 @@ Moreover, we find that `dolly-v2-3b` does not have some capabilities, such as we
 ### Dataset Limitations
 Like all language models, `dolly-v2-3b` reflects the content and limitations of its training corpuses.
-- **The Pile**: GPT-J’s pre-training corpus contains content mostly collected from the public internet, and like most web-scale datasets,
 it contains content many users would find objectionable. As such, the model is likely to reflect these shortcomings, potentially overtly
 in the case it is explicitly asked to produce objectionable content, and sometimes subtly, as in the case of biased or harmful implicit
 associations.

 # dolly-v2-3b Model Card
 ## Summary
+Databricks' `dolly-v2-3b`, an instruction-following large language model trained on the Databricks machine learning platform
 that is licensed for commercial use. Based on `pythia-2.8b`, Dolly is trained on ~15k instruction/response fine tuning records
 [`databricks-dolly-15k`](https://github.com/databrickslabs/dolly/tree/master/data) generated
 by Databricks employees in capability domains from the InstructGPT paper, including brainstorming, classification, closed QA, generation,
 ## Model Overview
 `dolly-v2-3b` is a 2.8 billion parameter causal language model created by [Databricks](https://databricks.com/) that is derived from
+[EleutherAI's](https://www.eleuther.ai/) [Pythia-2.8b](https://huggingface.co/EleutherAI/pythia-2.8b) and fine-tuned
 on a [~15K record instruction corpus](https://github.com/databrickslabs/dolly/tree/master/data) generated by Databricks employees and released under a permissive license (CC-BY-SA)
 ## Usage
 ### Dataset Limitations
 Like all language models, `dolly-v2-3b` reflects the content and limitations of its training corpuses.
+- **The Pile**: GPT-J's pre-training corpus contains content mostly collected from the public internet, and like most web-scale datasets,
 it contains content many users would find objectionable. As such, the model is likely to reflect these shortcomings, potentially overtly
 in the case it is explicitly asked to produce objectionable content, and sometimes subtly, as in the case of biased or harmful implicit
 associations.