HyperionHF
commited on
Commit
•
2afdf75
1
Parent(s):
65aab31
Add colab link
Browse files
README.md
CHANGED
@@ -25,6 +25,8 @@ This model is a fine-tune of [codegen-350m-mono](https://huggingface.co/Salesfor
|
|
25 |
|
26 |
diff-codegen-350m-v2 is an experimental research artifact and should be treated as such. We are releasing these results and this model in the hopes that it may be useful to the greater research community, especially those interested in LMs for code.
|
27 |
|
|
|
|
|
28 |
## Training Data
|
29 |
|
30 |
This model is a fine-tune of [codegen-350m-mono](https://huggingface.co/Salesforce/codegen-350M-mono) by Salesforce. This language model was first pre-trained on The Pile, an 800Gb dataset composed of varied web corpora. The datasheet and paper for the Pile can be found [here](https://arxiv.org/abs/2201.07311) and [here](https://arxiv.org/abs/2101.00027) respectively. The model was then fine-tuned on a large corpus of code data in multiple languages, before finally being fine-tuned on a Python code dataset. The Codegen paper with full details of these datasets can be found [here](https://arxiv.org/abs/2203.13474).
|
|
|
25 |
|
26 |
diff-codegen-350m-v2 is an experimental research artifact and should be treated as such. We are releasing these results and this model in the hopes that it may be useful to the greater research community, especially those interested in LMs for code.
|
27 |
|
28 |
+
An example Colab notebook with a brief example of prompting the model is [here](https://colab.research.google.com/drive/1ySm6HYvALerDiGmk6g3pDz68V7fAtrQH#scrollTo=thvzNpmahNNx).
|
29 |
+
|
30 |
## Training Data
|
31 |
|
32 |
This model is a fine-tune of [codegen-350m-mono](https://huggingface.co/Salesforce/codegen-350M-mono) by Salesforce. This language model was first pre-trained on The Pile, an 800Gb dataset composed of varied web corpora. The datasheet and paper for the Pile can be found [here](https://arxiv.org/abs/2201.07311) and [here](https://arxiv.org/abs/2101.00027) respectively. The model was then fine-tuned on a large corpus of code data in multiple languages, before finally being fine-tuned on a Python code dataset. The Codegen paper with full details of these datasets can be found [here](https://arxiv.org/abs/2203.13474).
|