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@@ -7,7 +7,7 @@ python convert-to-torch.py models/opt-1.3b
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The output will be written to torch-dumps/name-of-the-model.pt
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'''
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-from transformers import AutoModelForCausalLM, T5ForConditionalGeneration
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+from transformers import AutoModelForCausalLM
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import torch
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from sys import argv
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from pathlib import Path
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@@ -16,10 +16,7 @@ path = Path(argv[1])
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model_name = path.name
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print(f"Loading {model_name}...")
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-if model_name in ['flan-t5', 't5-large']:
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- model = T5ForConditionalGeneration.from_pretrained(path).cuda()
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-else:
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- model = AutoModelForCausalLM.from_pretrained(path, low_cpu_mem_usage=True, torch_dtype=torch.float16).cuda()
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+model = AutoModelForCausalLM.from_pretrained(path, low_cpu_mem_usage=True, torch_dtype=torch.float16).cuda()
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print("Model loaded.")
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print(f"Saving to torch-dumps/{model_name}.pt")
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