65 lines
1.5 KiB
Markdown
65 lines
1.5 KiB
Markdown
---
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language:
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- ko
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library_name: transformers
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pipeline_tag: text-generation
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license: cc-by-nc-sa-4.0
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---
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**The license is `cc-by-nc-sa-4.0`.**
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# **🐻❄️You_can_cry_Snowman-13B🐻❄️**
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## Model Details
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**Model Developers** Seungyoo Lee(DopeorNope)
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I am in charge of Large Language Models (LLMs) at Markr AI team in South Korea.
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**Input** Models input text only.
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**Output** Models generate text only.
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**Model Architecture**
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You_can_cry_Snowman-13B is an auto-regressive language model based on the SOLAR architecture.
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---
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## **Base Model**
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[kyujinpy/Sakura-SOLAR-Instruct](https://huggingface.co/kyujinpy/Sakura-SOLAR-Instruct)
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[Weyaxi/SauerkrautLM-UNA-SOLAR-Instruct](https://huggingface.co/Weyaxi/SauerkrautLM-UNA-SOLAR-Instruct)
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## **Implemented Method**
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I have merged two models by increasing the parameter size to create a larger model.
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I wanted to check how much the performance of the SOLAR base model changes when the scale of the parameters is increased.
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---
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# Implementation Code
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## Load model
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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repo = "DopeorNope/You_can_cry_Snowman-13B"
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OpenOrca = AutoModelForCausalLM.from_pretrained(
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repo,
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return_dict=True,
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torch_dtype=torch.float16,
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device_map='auto'
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)
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OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
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```
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--- |