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llama-v13a-6000

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README.md ADDED
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+ ---
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+ library_name: peft
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+ ---
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+ ## Training procedure
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+
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+
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+ The following `bitsandbytes` quantization config was used during training:
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+ - quant_method: gptq
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+ - bits: 4
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+ - tokenizer: None
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+ - dataset: None
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+ - group_size: 512
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+ - damp_percent: 0.01
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+ - desc_act: True
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+ - sym: True
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+ - true_sequential: True
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+ - use_cuda_fp16: False
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+ - model_seqlen: None
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+ - block_name_to_quantize: None
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+ - module_name_preceding_first_block: None
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+ - batch_size: 1
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+ - pad_token_id: None
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+ - disable_exllama: True
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+ - max_input_length: None
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+
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+ The following `bitsandbytes` quantization config was used during training:
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+ - quant_method: gptq
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+ - bits: 4
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+ - tokenizer: None
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+ - dataset: None
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+ - group_size: 512
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+ - damp_percent: 0.01
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+ - desc_act: True
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+ - sym: True
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+ - true_sequential: True
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+ - use_cuda_fp16: False
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+ - model_seqlen: None
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+ - block_name_to_quantize: None
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+ - module_name_preceding_first_block: None
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+ - batch_size: 1
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+ - pad_token_id: None
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+ - disable_exllama: True
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+ - max_input_length: None
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+ ### Framework versions
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+
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+ - PEFT 0.6.0.dev0
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+
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+ - PEFT 0.6.0.dev0
adapter_config.json ADDED
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+ "base_model_name_or_path": "llama2-70B-gptq-4bit",
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+ "bias": "none",
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+ "lora_alpha": 64,
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+ "lora_dropout": 0.0,
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+ "peft_type": "LORA",
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+ "r": 2,
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+ "target_modules": [
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+ "gate_proj",
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+ "up_proj"
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+ ],
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+ "task_type": "CAUSAL_LM"
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+ }
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+ "sp_model_kwargs": {},
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+ "tokenizer_class": "LlamaTokenizer",
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