初始化项目，由ModelHub XC社区提供模型
Model: HenryJJ/Instruct_Yi-6B_Dolly_CodeAlpaca Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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datasets:
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- databricks/databricks-dolly-15k
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- lucasmccabe-lmi/CodeAlpaca-20k
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---
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# Instruct_Yi-6B_Dolly15K
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Fine-tuned from Yi-6B， used Dolly15k for the dataset. 90% for training, 10% validation. Trained for 2.0 epochs using Lora. Trained with 2048 context window. Compared with https://huggingface.co/HenryJJ/Instruct_Yi-6B_Dolly15K, I add additional CodeAlpaca_20K dataset that good at coding.
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# Model Details
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* **Trained by**: trained by HenryJJ.
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* **Model type:** **Instruct_Yi-6B_Dolly15K** is an auto-regressive language model based on the Llama 2 transformer architecture.
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* **Language(s)**: English
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* **License for Instruct_Yi-6B_Dolly15K**: apache-2.0 license
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# Prompting
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## Prompt Template With Context
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<|startoftext|>[INST]{instruction} {context}[/INST]{response}<|endoftext|>
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```
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<|startoftext|>[INST]
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Write a 10-line poem about a given topic
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The topic is about racecars
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[/INST]
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```
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## Prompt Template Without Context
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```
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<|startoftext|>[INST]
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Who was the was the second president of the United States?
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[/INST]
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```
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# Training script:
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Fully opensourced at: https://github.com/hengjiUSTC/learn-llm/blob/main/trl_finetune.py. Run on aws g4dn.12xlarge instance for 10 hours.
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```
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python3 trl_finetune.py --config configs/yi_6b-large.yml
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```
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config.json
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"_name_or_path": "01-ai/Yi-6B",
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"architectures": [
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"LlamaForCausalLM"
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],
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"transformers_version": "4.36.2",
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"vocab_size": 64000
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}
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174133
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174133
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Load Diff
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40
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"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|endoftext|>",
|
||||
"legacy": true,
|
||||
"model_max_length": 4096,
|
||||
"pad_token": "<unk>",
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user