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Update documentation
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@ -177,7 +177,7 @@ Optionally, you can use the following command-line flags:
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| `--cpu` | Use the CPU to generate text.|
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| `--load-in-8bit` | Load the model with 8-bit precision.|
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| `--wbits WBITS` | GPTQ: Load a pre-quantized model with specified precision in bits. 2, 3, 4 and 8 are supported. |
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| `--model_type MODEL_TYPE` | GPTQ: Model type of pre-quantized model. Currently only LLaMA and OPT are supported. |
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| `--model_type MODEL_TYPE` | GPTQ: Model type of pre-quantized model. Currently LLaMA, OPT, and GPT-J are supported. |
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| `--groupsize GROUPSIZE` | GPTQ: Group size. |
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| `--pre_layer PRE_LAYER` | GPTQ: The number of layers to preload. |
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| `--bf16` | Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU. |
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@ -48,7 +48,6 @@ def _load_quant(model, checkpoint, wbits, groupsize=-1, faster_kernel=False, exc
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return model
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def load_quantized(model_name):
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if not shared.args.model_type:
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# Try to determine model type from model name
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@ -84,7 +84,7 @@ parser.add_argument('--gptq-bits', type=int, default=0, help='DEPRECATED: use --
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parser.add_argument('--gptq-model-type', type=str, help='DEPRECATED: use --model_type instead.')
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parser.add_argument('--gptq-pre-layer', type=int, default=0, help='DEPRECATED: use --pre_layer instead.')
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parser.add_argument('--wbits', type=int, default=0, help='GPTQ: Load a pre-quantized model with specified precision in bits. 2, 3, 4 and 8 are supported.')
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parser.add_argument('--model_type', type=str, help='GPTQ: Model type of pre-quantized model. Currently only LLaMA and OPT are supported.')
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parser.add_argument('--model_type', type=str, help='GPTQ: Model type of pre-quantized model. Currently LLaMA, OPT, and GPT-J are supported.')
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parser.add_argument('--groupsize', type=int, default=-1, help='GPTQ: Group size.')
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parser.add_argument('--pre_layer', type=int, default=0, help='GPTQ: The number of layers to preload.')
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