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README.md
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---
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license: bigcode-openrail-m
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-
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tags:
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- generated_from_trainer
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model-index:
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- name: peft-lora-starcoder-chat-asst-A100-40GB-colab
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results: []
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- Pytorch 2.0.0
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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---
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license: bigcode-openrail-m
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library_name: peft
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tags:
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- generated_from_trainer
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base_model: bigcode/tiny_starcoder_py
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model-index:
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- name: peft-lora-starcoder-chat-asst-A100-40GB-colab
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results: []
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- Pytorch 2.0.0
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: bitsandbytes
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: True
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- bnb_4bit_compute_dtype: bfloat16
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### Framework versions
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- PEFT 0.6.3.dev0
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