add v2 model support
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@@ -14,7 +14,7 @@ def load_model_llama(*args, **kwargs):
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print("Loading {} ...".format(model_path))
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t0 = time.time()
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model, tokenizer = load_llama_model_4bit_low_ram(config_path, model_path)
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model, tokenizer = load_llama_model_4bit_low_ram(config_path, model_path, groupsize=-1)
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model = PeftModel.from_pretrained(model, lora_path, device_map={'': 0}, torch_dtype=torch.float32)
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print('{} Lora Applied.'.format(lora_path))
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@@ -22,7 +22,8 @@ def load_model_llama(*args, **kwargs):
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print('Apply auto switch and half')
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for n, m in model.named_modules():
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if isinstance(m, Autograd4bitQuantLinear) or isinstance(m, Linear4bitLt):
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m.zeros = m.zeros.half()
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if m.groupsize == -1:
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m.zeros = m.zeros.half()
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m.scales = m.scales.half()
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m.bias = m.bias.half()
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autograd_4bit.use_new = True
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