Use str(Path) instead of os.path.abspath(Path)
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b9e0712b92
commit
77294b27dd
3 changed files with 7 additions and 9 deletions
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@ -25,10 +25,10 @@ class RWKVModel:
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tokenizer_path = Path(f"{path.parent}/20B_tokenizer.json")
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if shared.args.rwkv_strategy is None:
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model = RWKV(model=os.path.abspath(path), strategy=f'{device} {dtype}')
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model = RWKV(model=str(path), strategy=f'{device} {dtype}')
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else:
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model = RWKV(model=os.path.abspath(path), strategy=shared.args.rwkv_strategy)
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pipeline = PIPELINE(model, os.path.abspath(tokenizer_path))
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model = RWKV(model=str(path), strategy=shared.args.rwkv_strategy)
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pipeline = PIPELINE(model, str(tokenizer_path))
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result = self()
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result.pipeline = pipeline
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@ -61,7 +61,7 @@ class RWKVTokenizer:
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@classmethod
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def from_pretrained(self, path):
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tokenizer_path = path / "20B_tokenizer.json"
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tokenizer = Tokenizer.from_file(os.path.abspath(tokenizer_path))
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tokenizer = Tokenizer.from_file(str(tokenizer_path))
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result = self()
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result.tokenizer = tokenizer
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@ -1,4 +1,3 @@
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import os
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import sys
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from pathlib import Path
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@ -7,7 +6,7 @@ import torch
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import modules.shared as shared
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sys.path.insert(0, os.path.abspath(Path("repositories/GPTQ-for-LLaMa")))
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sys.path.insert(0, str(Path("repositories/GPTQ-for-LLaMa")))
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from llama import load_quant
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@ -41,7 +40,7 @@ def load_quantized_LLaMA(model_name):
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print(f"Could not find {pt_model}, exiting...")
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exit()
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model = load_quant(path_to_model, os.path.abspath(pt_path), bits)
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model = load_quant(path_to_model, str(pt_path), bits)
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# Multi-GPU setup
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if shared.args.gpu_memory:
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