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Doge-20M-Instruct

Question Answering
Transformers
Safetensors
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doge
text-generation
custom_code
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Update README.md

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  1. README.md +7 -7
README.md CHANGED
@@ -5,7 +5,7 @@ datasets:
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  - HuggingFaceTB/smoltalk
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  - HuggingFaceH4/ultrafeedback_binarized
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  base_model:
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- - JingzeShi/Doge-20M
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  language:
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  - en
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  pipeline_tag: question-answering
@@ -26,8 +26,8 @@ In addition, Doge uses Dynamic Mask Attention as sequence transformation and can
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig, TextStreamer
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- tokenizer = AutoTokenizer.from_pretrained("JingzeShi/Doge-20M-Instruct")
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- model = AutoModelForCausalLM.from_pretrained("JingzeShi/Doge-20M-Instruct", trust_remote_code=True)
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  generation_config = GenerationConfig(
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  max_new_tokens=100,
@@ -70,14 +70,14 @@ We build the Doge-Instruct by first SFT on [SmolTalk](https://huggingface.co/dat
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  **SFT**:
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  | Model | Training Data | Epochs | Content Length | LR | Batch Size | Precision |
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  |---|---|---|---|---|---|---|
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- | [Doge-20M-Instruct-SFT](https://huggingface.co/JingzeShi/Doge-20M-Instruct-SFT) | [HuggingFaceTB/smoltalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk) | 2 | 2048 | 8e-4 | 0.25M | bfloat16 |
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- | [Doge-60M-Instruct](https://huggingface.co/JingzeShi/Doge-60M-Instruct) | [HuggingFaceTB/smoltalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk) | 2 | 2048 | 6e-4 | 0.25M | bfloat16 |
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  **DPO**:
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  | Model | Training Data | Epochs | Content Length | LR | Batch Size | Precision |
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  |---|---|---|---|---|---|---|
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- | [Doge-20M-Instruct](https://huggingface.co/JingzeShi/Doge-20M-Instruct) | [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) | 2 | 1024 | 8e-5 | 0.125M | bfloat16 |
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- | [Doge-60M-Instruct](https://huggingface.co/JingzeShi/Doge-60M-Instruct) | [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) | 2 | 1024 | 6e-5 | 0.125M | bfloat16 |
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  **Procedure**:
 
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  - HuggingFaceTB/smoltalk
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  - HuggingFaceH4/ultrafeedback_binarized
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  base_model:
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+ - SmallDoge/Doge-20M
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  language:
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  - en
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  pipeline_tag: question-answering
 
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig, TextStreamer
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+ tokenizer = AutoTokenizer.from_pretrained("SmallDoge/Doge-20M-Instruct")
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+ model = AutoModelForCausalLM.from_pretrained("SmallDoge/Doge-20M-Instruct", trust_remote_code=True)
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  generation_config = GenerationConfig(
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  max_new_tokens=100,
 
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  **SFT**:
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  | Model | Training Data | Epochs | Content Length | LR | Batch Size | Precision |
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  |---|---|---|---|---|---|---|
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+ | [Doge-20M-Instruct-SFT](https://huggingface.co/SmallDoge/Doge-20M-Instruct-SFT) | [HuggingFaceTB/smoltalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk) | 2 | 2048 | 8e-4 | 0.25M | bfloat16 |
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+ | [Doge-60M-Instruct](https://huggingface.co/SmallDoge/Doge-60M-Instruct) | [HuggingFaceTB/smoltalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk) | 2 | 2048 | 6e-4 | 0.25M | bfloat16 |
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  **DPO**:
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  | Model | Training Data | Epochs | Content Length | LR | Batch Size | Precision |
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  |---|---|---|---|---|---|---|
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+ | [Doge-20M-Instruct](https://huggingface.co/SmallDoge/Doge-20M-Instruct) | [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) | 2 | 1024 | 8e-5 | 0.125M | bfloat16 |
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+ | [Doge-60M-Instruct](https://huggingface.co/SmallDoge/Doge-60M-Instruct) | [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) | 2 | 1024 | 6e-5 | 0.125M | bfloat16 |
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  **Procedure**: