Trivial: standardize single curly quotes (don't ask)
This commit is contained in:
parent
d0aa7ea43d
commit
43925aa353
@ -10,7 +10,7 @@ datasets:
|
|||||||
# dolly-v2-12b Model Card
|
# dolly-v2-12b Model Card
|
||||||
## Summary
|
## Summary
|
||||||
|
|
||||||
Databricks’ `dolly-v2-12b`, an instruction-following large language model trained on the Databricks machine learning platform
|
Databricks' `dolly-v2-12b`, an instruction-following large language model trained on the Databricks machine learning platform
|
||||||
that is licensed for commercial use. Based on `pythia-12b`, Dolly is trained on ~15k instruction/response fine tuning records
|
that is licensed for commercial use. Based on `pythia-12b`, Dolly is trained on ~15k instruction/response fine tuning records
|
||||||
[`databricks-dolly-15k`](https://github.com/databrickslabs/dolly/tree/master/data) generated
|
[`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,
|
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
|
## Model Overview
|
||||||
`dolly-v2-12b` is a 12 billion parameter causal language model created by [Databricks](https://databricks.com/) that is derived from
|
`dolly-v2-12b` is a 12 billion parameter causal language model created by [Databricks](https://databricks.com/) that is derived from
|
||||||
[EleutherAI’s](https://www.eleuther.ai/) [Pythia-12b](https://huggingface.co/EleutherAI/pythia-12b) and fine-tuned
|
[EleutherAI's](https://www.eleuther.ai/) [Pythia-12b](https://huggingface.co/EleutherAI/pythia-12b) 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)
|
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
|
## Usage
|
||||||
@ -139,7 +139,7 @@ Moreover, we find that `dolly-v2-12b` does not have some capabilities, such as w
|
|||||||
### Dataset Limitations
|
### Dataset Limitations
|
||||||
Like all language models, `dolly-v2-12b` reflects the content and limitations of its training corpuses.
|
Like all language models, `dolly-v2-12b` 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,
|
- **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
|
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
|
in the case it is explicitly asked to produce objectionable content, and sometimes subtly, as in the case of biased or harmful implicit
|
||||||
associations.
|
associations.
|
||||||
|
Loading…
x
Reference in New Issue
Block a user