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README.md

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+---
+library_name: peft
+---
+## Training procedure
+
+
+The following `bitsandbytes` quantization config was used during training:
+- quant_method: gptq
+- bits: 4
+- tokenizer: None
+- dataset: None
+- group_size: 128
+- damp_percent: 0.01
+- desc_act: False
+- sym: True
+- true_sequential: True
+- use_cuda_fp16: False
+- model_seqlen: None
+- block_name_to_quantize: None
+- module_name_preceding_first_block: None
+- batch_size: 1
+- pad_token_id: None
+- disable_exllama: True
+### Framework versions
+
+
+- PEFT 0.5.0

adapter_config.json

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+{
+  "auto_mapping": null,
+  "base_model_name_or_path": "TheBloke/Llama-2-7b-Chat-GPTQ",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 32,
+  "lora_dropout": 0.05,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "revision": null,
+  "target_modules": [
+    "k_proj",
+    "o_proj",
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

adapter_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:611016ce6472e54efb99d9d7620fe8928e31ab59cb4648c2d89c8fd4c0e95d11
+size 33646413