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| This is a Finetuning of GPT-J-6B using LoRa - https://huggingface.co/EleutherAI/gpt-j-6B |
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| The dataset is the cleaned version of the Alpaca dataset - https://github.com/gururise/AlpacaDataCleaned |
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| A model similar to this has been talked about |
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| The performance is good but not as good as the orginal Alpaca trained from a base model of LLaMa |
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| This is mostly due to the LLaMa 7B model being pretrained on 1T tokens and GPT-J-6B being trained on 300-400M tokens |
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| You will need a 3090 or A100 to run it, unfortunately this current version won't work on a T4. |
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| --- |
| library_name: peft |
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - Text Generation |
| --- |
| ## Training procedure |
| |
| |
| The following `bitsandbytes` quantization config was used during training: |
| - load_in_8bit: True |
| - load_in_4bit: False |
| - llm_int8_threshold: 6.0 |
| - llm_int8_skip_modules: None |
| - llm_int8_enable_fp32_cpu_offload: False |
| - llm_int8_has_fp16_weight: False |
| - bnb_4bit_quant_type: fp4 |
| - bnb_4bit_use_double_quant: False |
| - bnb_4bit_compute_dtype: float32 |
| |
| The following `bitsandbytes` quantization config was used during training: |
| - load_in_8bit: True |
| - load_in_4bit: False |
| - llm_int8_threshold: 6.0 |
| - llm_int8_skip_modules: None |
| - llm_int8_enable_fp32_cpu_offload: False |
| - llm_int8_has_fp16_weight: False |
| - bnb_4bit_quant_type: fp4 |
| - bnb_4bit_use_double_quant: False |
| - bnb_4bit_compute_dtype: float32 |
| |
| The following `bitsandbytes` quantization config was used during training: |
| - load_in_8bit: True |
| - load_in_4bit: False |
| - llm_int8_threshold: 6.0 |
| - llm_int8_skip_modules: None |
| - llm_int8_enable_fp32_cpu_offload: False |
| - llm_int8_has_fp16_weight: False |
| - bnb_4bit_quant_type: fp4 |
| - bnb_4bit_use_double_quant: False |
| - bnb_4bit_compute_dtype: float32 |
| ### Framework versions |
| |
| - PEFT 0.4.0.dev0 |
| - PEFT 0.4.0.dev0 |
| |
| - PEFT 0.4.0.dev0 |
