Upload README.md

README.md

@@ -6,7 +6,7 @@ license_link: LICENSE
 license_name: deepseek-license
 model_creator: DeepSeek
 model_name: Deepseek Coder 33B Base
-model_type: llama
+model_type: deepseek
 prompt_template: '{prompt}
 
   '
@@ -62,15 +62,8 @@ These files were quantised using hardware kindly provided by [Massed Compute](ht
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-<!-- licensing start -->
-## Licensing
 
-The creator of the source model has listed its license as `other`, and this quantization has therefore used that same license.
 
-As this model is based on Llama 2, it is also subject to the Meta Llama 2 license terms, and the license files for that are additionally included. It should therefore be considered as being claimed to be licensed under both licenses. I contacted Hugging Face for clarification on dual licensing but they do not yet have an official position. Should this change, or should Meta provide any feedback on this situation, I will update this section accordingly.
-
-In the meantime, any questions regarding licensing, and in particular how these two licenses might interact, should be directed to the original model repository: [DeepSeek's Deepseek Coder 33B Base](https://huggingface.co/deepseek-ai/deepseek-coder-33b-base).
-<!-- licensing end -->
 
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@@ -373,9 +366,9 @@ And thank you again to a16z for their generous grant.
 
 ### 1. Introduction of Deepseek Coder
 
-Deepseek Coder comprises a series of code language models trained on both 87% code and 13% natural language in English and Chinese, with each model pre-trained on 2T tokens. We provide various sizes of the code model, ranging from 1B to 33B versions. Each model is pre-trained on project-level code corpus by employing a window size of 16K and a extra fill-in-the-blank task, to support  project-level code completion and infilling. For coding capabilities, Deepseek Coder achieves state-of-the-art performance among open-source code models on multiple programming languages and various benchmarks. 
+Deepseek Coder is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language in both English and Chinese. We provide various sizes of the code model, ranging from 1B to 33B versions. Each model is pre-trained on project-level code corpus by employing a window size of 16K and a extra fill-in-the-blank task, to support  project-level code completion and infilling. For coding capabilities, Deepseek Coder achieves state-of-the-art performance among open-source code models on multiple programming languages and various benchmarks. 
 
-- **Massive Training Data**: Trained on 2T tokens, including 87% code and 13% linguistic data in both English and Chinese languages.
+- **Massive Training Data**: Trained from scratch on 2T tokens, including 87% code and 13% linguistic data in both English and Chinese languages.
   
 - **Highly Flexible & Scalable**: Offered in model sizes of 1.3B, 5.7B, 6.7B, and 33B, enabling users to choose the setup most suitable for their requirements.